The Times, They Have A-Changed, Part I

"This technology revolution was not invented by robo-advisers. They have simply noticed, and taken advantage of, a broader and deeper shift towards passive investment through ETFs and index funds."

-- John Gapper, Robots are Better Investors than People

We like to think of "technology revolutions", but as Mr. Gapper points out, revolutions aren't led by technology. The landscape is littered with shuttered technology companies that showed that a thing was possible, but failed to foment a "revolution".

Revolutions happen once we have critical mass of people with different attitudes and behaviors. Consider the changes in investing behaviors referred to above. Once investors realized that actively managed funds charged higher fees but performed no better (and frequently worse) than passively managed funds, they switched. Today, as investors come to realize that financial advisors are charging fees for putting their money in passive funds, they're amenable to robo-advisors that charge lower fees for doing exactly the same thing.

A change from human advisor to robo-investing won't happen at the pace set by technology, however. It took a long time for investors to change their preference from active to passive funds. Index funds first appeared in the 1970s, as did research showing that active funds didn't consistently outperform the broader market. Yet it took decades for investors to invest differently.

Why did it take so long? Attitudes, prejudices and predispositions take a long time to change. Sometimes they don't: those who hold a belief may never let it go, even in the face of overwhelming evidence to the contrary. And, people financially, politically or emotionally invested in something will fight to preserve it. Active fund managers initially derided passive funds, while today, facing massive capital outflows, they're fighting for survival. Those who stand to lose from change will also fight back with marketing designed to co-opt the next generation, such as the way manufacturers of sweet fizzy drinks simultaneously play to an older generation's nostalgia while encouraging them to create a sentimental moment - vis-a-vis their product - with a grandchild.

No matter how much technology we throw at something, entrenched behaviors don't start to change until a generation comes along that isn't as emotionally committed to them. And that still only describes how change starts, not how it finishes - and it can take a very long time to run its course. To understand the dynamics of change, we need to look at both ends of the generational spectrum: as people enter, people also leave. This is most obvious in the workforce where, in general, people join around age 18 and leave around age 65.

The United States has just completed a major generational shift, not so much for the one arriving as the one that has recently left.

The Great Depression and the Second World War shaped American domestic and foreign policy well into the 1990s. Yet as long ago as 1965, America had reared a generation without any direct experience of either, making them less constrained by the values held by the people who had come before them. And, starting 1965, a generation began to arrive born to parents who were themselves bred following the Depression-and-WW II-era. Prior to 1945, most everybody had direct experience to the privations of one or both. After 1965, we had generations grow up in households where those two seminal events were things their grandparents told them about from time to time, and which they only briefly studied in high school history classes.

Despite the social upheaval that coincided with the maturation of this post-depression-and-war generation (the late 1960s), the value system of the pre-1965 generation dominated American society and the American workplace, first through sheer numbers (those who held it made up the bulk of the working population) and later through positions of seniority (older people were more likely to hold executive positions).

The numbers are now vastly different. People born in 1945 reached age 65 in 2010. There are very few in the American workforce with a direct experience of life during WWII, let alone the Great Depression. Nor are there too many who are just one generation removed from those events (that is, grew up in households directly influenced by them); those who are one-generation-removed will largely exit the American workforce by 2030.

It's no coincidence that we've seen more change in the last decade than we arguably did in the three previous decades combined. But not so much because of a new generation arriving, bringing with it new expectations and demands, as much as the old generations leaving and relinquishing the top rung of authority and social influence. Out of numbers and out of power, those value systems no longer hold sway. Although we live and work in a "post-1965" world today, it took over 40 years - two additional generations - for that to happen.

Because change is a function of society more than technology, it's slow in coming but swift once it arrives. And, while a lot of change happened with the completion of the pre- to post-1965 shift (at least, in the workforce), the stage is set for still more revolutionary change. We'll look at specific examples in the next post.

How an Operational Gap Becomes a Generation Gap Becomes a Valuation Gap

A decade or so ago, when an IT organization (captive or company) hit rock bottom - bloated payroll, lost confidence and ruptured trust resulting from rampant defects, rocky deployments, functional mis-fits, and long delivery cycles - it would give anything a try, even that crazy Agile stuff. It didn't matter if it was incumbent management with their backs against the wall, or new management brought in to clean house, desperate times called for desperate measures. To people looking to shake things up, Agile made intuitive sense and a lot of it was appealing, even if its proponents had a bit too much evangelical zeal and some of it sounded a little strange. So they'd bite the bullet and do it, selectively anyway: a build server was easy to provision; releasing software for testing every couple of weeks was done easily enough, and getting everybody in the same physical workspace (or at least in close proximity to one another) could be done with a little arm-twisting; of course, developers were instructed to only pair program "opportunistically", and automating QA was a fight nobody wanted to fight, so they'd sit with the team and test incrementally but go on testing the way they always had. Still, even with compromises, there was a good story to tell, usually to do with much higher quality and eliminating rework, and that made Agile A Good Thing for all parties concerned.

Fast forward to today, and we see that Agile is much more ambitious. A few short years ago we were content to have an automated build execute every few minutes; today we want every check-in to trigger a build that is promoted through progressively more complex tests in virtual environments managed, instantiated and torn down by scripts. We used to be content releasing for user testing every other week, and to production every couple of months; we now aspire to release to production many times a day. We used to want Master Story Lists to guide incremental development; today we want to iteratively experiment through code and have the feedback inform requirements definition and prioritization. We used to be satisfied with better delivery of internally-facing software; today we want to evolve software products that are used by people across our ecosystem, from interested parties to customers to investors to employees. Today, Agile wants to push against everything that creates an artificial or temporal constraint, be it organization, management, accounting policy, or even capital structure.

Although Agile has evolved, the entire tech world hasn't moved with it. In fact, some of it hasn't moved at all: it's still common to see non-Agile organizations that do big up-front design; work in functional and skill silos; have manual builds, deployments and testing; and make "big bang" releases. And, it's still common for them to face a "rock bottom" moment where they conclude maybe it's finally time to look into this Agile stuff.

As hard as it was a decade ago to inject Agile into a non-Agile organization, it's much harder today for a non-Agile organization to complete a transformation. This seems counterintuitive: since the non-Agile to Agile path is so well trod, it should be much easier than it was in those pioneering days of yore. Although there's never been more tools, frameworks, languages, books, blogs, and countless other resources available to the individual practitioner aspiring to work differently, organizational change tends not to be self-directed. The challenge isn't taking an organization through the same well-established game plan, it's finding the people - the transformational leaders - who are willing to shepherd it through its journey.

Unfortunately, re-living the same internal negotiations to reach the same compromises, solving technical and organizational problems long ago solved, only to end up with an operating model that is considerably far short of the state-of-practice today is not a destination opportunity for an experienced change leader. Even assuming, as my colleague Alan Fiddes pointed out, that the change agents brought in still have the vocabulary to carry on arguments last fought so long ago, any change agent worth their salt isn't going to reset their career clock back a decade, no matter the financial inducement.

This might simply mean that the approach to change itself is what has to change: require far less shepherding from without by expecting more self-directed change from within, brought about by setting the right goals, creating the right incentives (motivate people) and measuring the right things (what gets measured is what gets managed). Why shouldn't it be self-directed? It isn't unreasonable to expect people in a line of work as dynamic as software development to keep their skills sharp and practices current. For people leading an organization that's a little dated in how it develops software, then, the question to hold people to isn't "why aren't you doing Agile" but "we're going to deploy any time and all the time effective fiscal Q3, so how are you going to operate to be able to support that?" It's amazing what people will do when sufficiently motivated, change agents be damned.

Whether there's a more effective means of change or not, being far adrift of the state of practice points to a more severe threat to the business as a whole: a generation gap.

* * *

Three decades ago, the state of practice didn't vary that much across companies. Yes, there were people coding C over Rdb deployed in VMS on minicomputers and people coding COBOL over IMS deployed in OS/390 on mainframes, but the practice landscape wasn't especially diverse: waterfall prevailed and a lot of code was still data-crunching logic run in batch. At the time, captive IT, consulting firms, governments, new tech firms (think Microsoft in the mid-80s), and established tech stalwarts (H-P, IBM) could reasonably expect to compete for the same labor. College grads in Computer Science or Management Information Systems learned practices that reinforced the modus operandi common to all consumers of business computing.

The landscape has changed. Practices are far less homogeneous, as they've had to evolve to accommodate a diverse community of interactive users pushing for features and functionality with little tolerance for failure. The familiar combatants still slug it out for labor, but must now also compete against tech product firms untethered to any legacy practices, norms, policies or technologies. Today's grads are trained in new practices and expect their employer to practice them, too.

Companies lagging behind in their state of practice will struggle to compete for newly minted labor: why would somebody with highly marketable tech skills go to work at a place stuck in the past, when they can work in a more current - even cutting edge - environment?

This isn't just a hiring problem. A practice gap is fuel for a generation gap if it deflects young, skilled people from becoming employees. By failing to hire the next generation employee, a company develops an intrinsic inability to understand its next generation customer.

A company isn't going to reach a new generation of buyer - consumer or business - if it is tone deaf to them. A company ignorant of the next generation's motivations, desires, values and expectations has little chance of recognizing what it isn't doing to win their attention, let alone their business. Since social systems are self-reinforcing, a company is unlikely to break the deadlock of ignorance and inaction.

Failing to bridge a generation gap not only cuts a business off from growth opportunities, it sets the stage for long-term irrelevance. Investors recognize this, even when management does not. Growth changes from being a "risk" to being an "uncertainty", and when that happens a company's future¹ is no longer priced at a premium, but a discount. In this way, an operational gap becomes a generation gap becomes a valuation gap.

Outdated practices are an indicator that management has it's head buried in the sand: it has a problem it can't see, that it doesn't know how to solve, that is starved for information it can't get because it has elected to disassociate itself from its source. The motivation to change how you practice shouldn't be to become more competitive today, but to still be relevant tomorrow.

 

 

¹ By way of example, Yahoo net of its Alibaba holding and cash has frequently been valued at or near $0 by investors in recent years.

Are Microservices to Ecosystems as Core Competencies were to Conglomerates?

As far back as the 19th century, industrial firms pursued vertical integration strategies. The thinking was that by owning the supply chain from raw materials to retail outlets, a firm had direct control over its entire cost structure, making it better able to squeeze efficiencies out of it and being less susceptible to supply shocks. This was important because, for large industrial firms, competing on price was the primary strategy for winning market share.

During the 1950's and 60's, companies also pursued conglomerate strategies: bringing seemingly unrelated businesses under one roof, sometimes seeking synergies (as Sears did owning a retail merchandiser and retail brokerage - "buy your stocks where you buy your socks"), and sometimes not (as LTV did owning a steel company and an airline). The rationale for the conglomerate was entirely financial: cheap (mostly debt) capital allowed large companies to grow through acquisition, and regulators were less likely to block acquisitions of unrelated firms on monopolistic grounds.

By the 1980s, both strategies had begun to lose favor. The financial benefit had evaporated: high interest rates clobbered the profits of debt-fueled acquisitions and forced divestiture. But the operating benefits weren't there, either. Different types of businesses (manufacturing, distribution, retail) require different types of leadership and have very different cultures. And, within each of those businesses, some functions are differentiating (such as fleet optimization for a logistics company) while some functions are not (nobody beats their competitors by having a superior accounting back office). Management thinking embraced "core competencies": own and hone the things that differentiate, rent and commoditize the things that do not. This also allowed for better matching of capital with company: the risks and returns from a company that owns a fleet of railcars is easier to assess than the risks and returns from a company that owns ore mines, railcars, and foundries. By breaking them up, the individual investor can choose what types of businesses to expose their capital to (a raw materials company, or an asset company, or a refining company), and the pricing of that capital more accurately reflects the risks.

Tech firms today are embracing the "vertical integration" and "conglomerate" strategies of yore by positioning themselves as "platform" and "ecosystem" companies. The thinking is that by combining multiple and diverse capabilities into a single offering, a company creates both efficiencies and synergistic value for counterparties in some activity, such as crowdsource funding or payments. The ecosystem strategy takes this even further, combining unrelated capabilities under one roof (eBay buying Skype in 2005, SAP developing HANA in 2010, Facebook buying Oculus in 2014), often justifiable if only because digital commerce is still in its infancy and nobody is really sure what's going to work and what's not.

But what if you could extract utility-like functionality from within an ecosystem into an independent company? Take payroll as an example: rather than have every Human Resources platform company need its own team of people to write and maintain state and federal witholding rules, hive those off into an independent business that makes them available as a metered service offering, charging a tiny usage tax (say, $0.001) each time it's invoked. The technology to do this is certainly available: code the algorithms as a microservice or a blockchain smart contract, and deploy them in an elastic cloud environment (as usage will tend to spike with pay cycles).

To the HR platform company, there are a lot of good reasons to do this. It monetizes a non-value generative activity (nobody subscribes to a payroll system because their implementation of the witholding rules are better than everybody else's). It throws off utility-like revenue streams that move in lock step with the broader job market. It disaggregates a staid HR utility function that needs to be deployed infrequently (potentially only as often as once per year, when new tax laws come into effect) from more innovative ones that are more exploratory in nature and demand frequent deployments (such as time entry performed through emerging wearable tech). It separates a legacy and risk-averse tech culture from a cutting-edge risk-prone one. It takes a high fixed cost for maintaining a non-differentiating characteristic off the P&L (teams maintaining rule-heavy legacy code are rarely inexpensive). It's stable cash flows would be attractive to debt finance, better aligning capital investment in HR technology. It removes asymmetric risk that can be more accurately insured (smothered in a platform, correct calculations offer no financial upside, while a faulty calculation exposes it to costly litigation and reputational damage).

True, it eliminates a barrier to entry of future competitors. And, while the market would support a handful of utilities to prevent monopoly, thin competition would give those utilities oligopic pricing power. But it creates a one-time financial windfall for the first movers, laggards would be pressured to subscribe by shareholders demanding the same structural benefits to the income statement, and low switching costs would keep utility pricing power in check.

Given that tech is in a period of both cheap capital (interest rates remain low, VC levels remain high, and companies such as Alibaba and Facebook can make acquisitions inexpensively with their own high-priced shares) and rapid growth (growth in consumption of tech products such as social media today mirrors growth in consumption of manufactured goods in the 50s and 60s), it's little surprise that we're seeing a return to industrial strategies past. But technologies like microservices and blockchain could be the modern equivalent of "core competencies" to sweep through businesses. Blockchain proponents already champion the potential of decentralized autonomous organizations (DAOs). With MBAs now eschewing investment banking in favor of tech companies, financial engineering of this nature isn't too far away.

Counterfactuals

Earlier this year, my house should have burned to the ground.  A CR2032 battery exploded and caught fire in a confined place dense with flammable objects.  But my house didn't burn down: at the moment the battery exploded, I was sitting a few feet away from it. I heard a loud bang, investigated, and stamped out the fire within a few seconds.

I wasn't planning to be there at the time. A series of minor reschedules and reprioritizations had me sitting in my home office at the moment the battery exploded. I happened to be in the right place at the right time to prevent something from happening.  It was business as usual for the rest of the day.

There is no law or reason governing why I was there at the moment the battery exploded, or for the battery to have exploded at precisely that moment.  What if my schedule isn't rearranged and I'm not home when the battery explodes? What if it happens hours earlier or later when everybody is asleep in the house? I can't help but think that there are more quantum realities where something bad happened than there are where something bad did not happen.

But that isn't necessarily true.  The battery could have exploded at a time when nobody was around to put out the fire, but the ensuing fire may have simply died out causing no damage.  And maybe the chemical processes that triggered the explosion was itself an anomaly of circumstances set in motion by my presence in the room at that particular moment.  I have to be content with the only certainty I have, which is that a battery exploded and nothing bad happened.

Counterfactuals are messy because they're not provable.  Strategy and investing, execution and operations are loaded with counterfactuals.  They're each similarly messy because we don't really know what would have happened had we chosen another course of action.  Conventional wisdom says that Kodak should have bet on the digital technology they invented, and not dithered around with its legacy analogue business. But what if Kodak were to have invested heavily in digital and their distribution partners made good on their threats to shift the lucrative film processing business to Fuji?  Would Kodak's bet on the future have imploded for being starved of cash flow?  Hindsight isn't 20/20, it's narrative fallacy.

Just as it's difficult to have retrospective strategic certainty, it's next to impossible to forecast the outcomes of alternative paths, decisions or circumstances.  It sounds simple enough: invest in the highest-return opportunities, and consistently assess the performance of and the risks to delivery.  But we're forced to interpret and project from incomplete and imperfect information. Our plans and forecasts are just as likely to be narrative fallacy as fact-based assessments.  Microsoft paid dearly for Skype, but we can't know what might have been had it been acquired by Google or Facebook - and the possibilities may very well have justified the premium Microsoft paid.

The landscape of strategic software investing and governance is riddled with speculation.  As much as we would like to think we've made the best decision available to us, or dodged a bullet, we rarely know with certainty.  No matter how formulaic we're told that portfolio management or delivery operations can be, they will never be as optimal or predictable as promised, because business is imprecise and untidy.

Corporate Middle Management as an Autopoietic System

[T]he aim of such systems is ultimately to produce themselves: their own organization and identity is their most important product.

-- Gareth Morgan, Images of Organization, p. 236.

In the early 1970s, biologists Humberto Maturana and Francisco Varela coined the term autopoiesis to define the self-maintaining nature of living cells: biological cells produce the components that maintain the structure that creates more components (in this case, more cells). This is in contrast to allopoietic systems, which use components (raw materials such as silicon and plastic) to generate something (mobile phones and computers) which are distinct from the thing that created it (the factory where they are made).

In the mid-1980s, Gareth Morgan applied the concept of autopoiesis to organizational study.

They do so by engaging in circular patterns of interaction whereby change in one element of the system is coupled with changes elsewhere, setting up continuous patterns of interaction that are always self-referential. They are self-referential because a system cannot enter into interactions that are not specified in the pattern of relations that define its organization.

-- Ibid, p. 236

A few months ago, I described the organizational pathologies that we see in slow-growth, (mostly) equity funded firms: because it faces no real pressure (no credit rating to support, no competitive threats to revenue) it will suffer from operations bloat. A significant source of that bloat will be a large middle management.

Left unchecked, tech organizations will grow vertically around line activities (software products that support business functions) and horizontally around shared services (testing, infrastructure). They will also establish one or more program management offices to navigate delivery of complex business initiatives across the fractured organizational landscape. For every management expansion, there is an equal and opposite hiring spree. The host business will mirror tech's management structures, creating business product managers opposite technology line managers, and a business PMO responsible for business change management functions opposite the tech PMO responsible for delivery of tech assets. This management sprawl happens for a variety of reasons: people are promoted into management for fear they might quit, IT gets burned by a delivery failure and creates new hierarchy in response, a senior business manager doesn't want to be seen as mapping to a low level of the tech organization, a new boss prefers to delegate rather than get his hands dirty with the details, there is a low level of trust between tech and business and matching staff is how it maintains equilibrium, and so forth.

Middle management is not a value-generative function. Because they are not engineers or analysts, middle managers don't directly contribute to solution development. Instead, they negotiate on behalf of their sphere of responsibility with other middle managers. They create documentation templates, project control forms, release and implementation workflows, and program checklists to create contracts among other managers to secure the time and attention of the people who do contribute to solution development. These contracts implicitly protect every middle manager by sharing responsibility (my work was dependent on somebody else who failed to deliver) and deflecting responsibility (another initiative took priority so we had no choice but to let this other deadline slip). The web of contracts allows middle management to self-perpetuate.

[W]e can describe autopoietic systems as those producing more of their own complexity than the one produced by their environment.

-- Carlos Gershenson, Requisite Variety, Autopoiesis, and Self-Organization.

It also serves as the fuel for growth: perpetual negotiation spurs middle management to expand its library of templates, forms, workflows and checklists. That, in turn, adds to the structure, because it requires more middle managers to fill out more program documentation. For example, a few years ago, the logical database storage for a legacy asset was overwhelmed when a new type of transaction was implemented; since then, the infrastructure department requires every new initiative to complete a "long-term storage analysis forecast". But, some initiatives don't generate many transactions at all and will have little impact on storage allocated to any asset. The managers in those initiatives don't have to fill out a "long-term storage analysis forecast", but must still fill out a "storage analysis forecast exemption" form to document why management concluded the forecast document wasn't necessary.

In this way, middle management is autopoietic: based on a flow of documentation, it creates components (middle managers) that maintains the structure (the bloated middle management) that creates new components (more middle managers).

* * *

[T]he brain does not process information from an environment, and does not represent the environment in memory. Rather, it establishes and assigns patterns of variation and points of reference as expressions of its own mode of organization. The system thus organizes its environment as part of itself. If one thinks about it, the idea that the brain can make representations of its environment presumes some external point of reference from which it is possible to judge the degree of correspondence between the representation and the reality. This implicitly presumes that the brain must have a capacity to see and understand its world from a point of reference outside itself. Clearly this cannot be so[.]

-- Morgan, pages 237-8.

Suppose we want to introduce Agile into an organization because we want delivery to be more efficient and effective, and we want a better relationship between business and technology. One way we think we can do that is by simplifying our management processes and making them more collaborative, and Agile appears to offer us a means of doing that.

If we have a large middle management function, we can't expect that Agile will simplify our requirements, development, release, or change management activities. What we should expect is that Agile will get co-opted by the very structures that it is there to disrupt. A middle manager cannot comprehend Agile as a different means to an end, because the only end a middle manager is pursuing is successful contract negotiation with other middle managers. A release plan becomes a closed-ended project plan, Stories in an iteration become a commitment, tasks per each Story become the coin of negotiation with other managers for their "resources". Adopting Agile - everything from adaptive planning to continuous delivery - requires a level of abstract thinking about why we do the things we do and how they lead to a delivery outcome that will be well beyond that of an incumbent middle management. Any middle manager capable of abstract thinking will have left the organization long ago: survival requires concrete thinking within a very narrow scope of self-referential activity.

When we recognize that identity involves the maintenance of a recurring set of relations, we quickly see that the problem of change hinges on the way systems deal with variations that influence their current mode of operation. Our attention is thus drawn to system processes that try to maintain identity by ignoring or counteracting threatening fluctuations, and to the way variations can lead to the emergence of new modes of organization.

-- Ibid, p 239.

For a large middle management, Agile is not a welcome change. If we have business and tech people working together daily rather than having a temporally shifted conversation through documentation, if we have technology generalists rather than specialists, if we capture knowledge in automated tests and ops scripts, we need far less intermediation in the delivery process. This obviates the need for an expansive middle management function.

An autopoietic system is capable of autoimmune responses. Co-opting, described above, is one. Ignoring is another: enough people refusing to change can force management to re-think its commitment to that change. Subverting is a third: creating obstacles and impediments to change to sow uncertainty and doubt on its effectiveness are behaviors intended to reinforce middle management's identity. Autoimmune forces are powerful: a function that exists solely for its own perpetuation - even when not by charter, but as a matter of social contract among its members - will become shrill in its own defense.

The policeman is not here to create disorder. The policeman is here to preserve disorder.

-- Richard J. Daley, 48th Mayor of Chicago

What does change look like under these circumstances?

Clearly, it isn't willing acceptance by the incumbents. We can't expect actors in a system to accept change that results in the destruction of that system. As Upton Sinclair famously wrote, "it is difficult to get a man to understand something, when his salary depends upon his not understanding it."

By definition, change of an autopoietic system must be triggered internally, and happen as a result of randomness. Morgan argues that "random variation provides the seed of possibility that allows the emergence and evolution of new system identities." Random changes create the possibility of new relations, which, if they're not absorbed or stifled by other parts of the system, can lead to new identities. Morgan argues that "Human ideas and practices seem to develop in a similar manner, exerting a major transformational effect once they acquire a critical level of support." Nassim Taleb makes the same argument in his book, Fooled by Randomness.

The corporate change leader doesn't have the luxury of time for the forces of randomness to reform an entrenched middle management. There are two policies that can accelerate structural change: disallowing self-referential justification for middle management practices (that is, expanding its scope of reference so that every action must be justified by a delivery outcome, not a middle management negotiation), and aggressive dismantling of the middle management structures themselves. The prior, if not compromised, puts an incumbent invested in the status quo on the defensive and robs it of it's raison d'être. It also helps to identify people in middle management who are reformable and coachable. The latter reduces the need for the prior.

Bad events in organisations are generally the product of bad systems rather than bad people ... [W]e need to go on and ask what it is about modern corporate life that has made such misbehavior not only possible but appear increasingly common.

-- John Kay, Organisations advance by asking "what went wrong" rather than "who is to blame

It's hopeful to believe that an incumbent middle management will "see the light" once introduced to a different set of practices, mechanics and tools. But the broader corporate reality tells us otherwise. When we introduce change, we quickly come into direct conflict with a self-referential ecosystem that, despite obvious internal contradictions and shortcomings, has an extraordinarily strong survival instinct. We also discover latent, institutionalized corporate misanthropy directed at users, customers, suppliers and business partners. A change toward Agile, and the value system it represents, is less enabling, and more threatening, than we'd like to think. To be successful as change agents, we have to dismantle the structures, processes and people behind the status quo while simultaneously replacing them with a new normal.

Potential and Motivation

When a management with a reputation for brilliance tackles a business with a reputation for bad economics, it is the reputation of the business that remains intact.

-- Warren Buffett

For a business to have "potential", it needs opportunity, money, willingness, talent, and aptitude. Yes, a business without all of these things still has potential: it might be poorly funded but have knowledge-acquisitive people and a clear opportunity; it may have weak capability but good cash flow. But somebody agreeing to lead or acquire a business because of its "potential" still needs to compensate for deficiencies in any of these areas.

Potential needs a wake up call if it is to be realized. Sometimes, our source of motivation is external: new competitors, or a threat to our business model. It can be internal: an activist investor on the board forces the CEO to accept new operating targets.

Potential and motivation are both the purview of leadership. A good leader creates potential where there is none: putting someone in a stretch role, freeing capital for reinvestment through a restructuring, diversifying the product line by acquiring a business, hiring a strong product team to engineer and market new offerings. A good leader motivates with incentives and rewards, culture and risk-taking: define business objectives that require cleverness and innovation and not just operational efficiency; flatten and simplify the organization, distribute authority and responsibility; recognize team behaviors over individual heroism.

The intersection of motivation and potential is never as far down each axis as we hope because they're constrained by our ambition (or lack thereof), and by fear. We can't imagine things any different so we fail to define an opportunity. We see competitive threats developing but we lack the will to act. We are reluctant to make difficult staff cuts to free up money. We don't recognize the outdated skills of our people, the absence of abstract thinking, the dearth of current technologies and practices, so we do nothing to upgrade our talent base. We're afraid of offending our current employees by changing the compensation structure. We are more comfortable micromanaging, demanding commitment, and promoting people through hierarchy than we are giving people autonomy and rewarding them for innovation.

Worst of all is when we simply talk ourselves down: of course we want to get to such-and-such state someday, but we can't possibly make so much change so quickly. This amounts to regulatory capture of a leader's ambition - and by extension, of a business' potential - by the business itself.

The difference between a change leader and a caretaker isn't lofty vision or inspiring words, it's the ability to create maximum potential within the organization, and the motivatiors that drive people's behaviors and actions to realize it.

Capitalizing Tech in a Cloud / SaaS / Continuous Delivery World

Around 2010, when US companies could count on a recovering domestic economy, a weak US dollar, and growing emerging market economies, CFOs didn't need to work that hard to flatter the income statement. This has changed: the US recovery has been inconsistent, emerging markets are performing poorly and the US dollar is strong (taking the edge off overseas revenue). Plus, firms are carrying more debt than they were a few years ago, making the optics of the P&L that much more important.

One result of this is that tech capitalization is back. It never really disappeared, of course, it just wasn't as common. But while tech capitalization was dormant, tech has changed a lot - quite a lot, in fact.

First, Cloud, SaaS and BYOD change software and infrastructure from capital investments to rent expenses. Renting is an economic convenience more than it is a cost efficiency. Renting is no less expensive than owning (the person who rents a house has to cover the landlord's mortgage, capital improvements, taxes, etc. in the rent payment), so technology costs represent a larger - and discreetly measurable - operating expense. As an expense, it's increasingly being indexed to payroll (that is, headcount), which makes it more like a tax (I need one ERP user license for every employee in sales, so if my sales force grows, I need more licenses).

Second, Continuous Delivery - deploying software hourly or daily instead of monthly or quarterly - blurs the lines among traditional development stages. It makes our packages of deployable work far more atomic than the more traditionally coarse "release" or "project" level deployment. Plus, if we're experimenting through software to see whether there's a need (much less a solution) - something uniquely enabled by Continuous Delivery - our development can't be capitalized at all. It's R&D, which has to be expensed.

What does it mean? Well, we don't know. For one thing, we're not really there yet. We know that this echoes the supercycle of businesses separating into asset-light operating companies (e.g., retailers) and asset-heavy finance companies (e.g., REITs). But we also know that a lot of firms still license captive ERP systems (no SaaS), operate captive data centers (no Cloud), and issue hardware to employees (no BYOD). In development, Continuous Delivery is still more idea than implemented among firms predisposed to capitalize rather than expense their software development costs. The execution trend toward tech asset light matches - but lags - the financial trend.

For another, specifically with regard to capitalizing development, we fit Agile under FASB 350-40 without violating the intent of the original AICPA policy (SOP 98-1), but we never explicitly formulated policy to reflect how work got done in an Agile world. For as much as we made Agile perform better than Waterfall under capitalization policies (e.g., better opex/capex ratio), it's always been an ill-fitting Waterfall suit around an Agile body. Fast forward, an today we have Continuous Delivery, which takes Agile concepts of frequent delivery and Lean development practices to the next degree. This extends the already long tail: accounting policy (treatment) lags tech execution (Continuous Delivery is still wishful thinking in most firms) lags financial expectation (asset light).

But some things we do know, and point to what we should be paying attention to.

The CFOs interpretation of tech as a capital investment is not the same as tech as an operating expense or tech as a tax. The more tech becomes an expense or a tax, the more downward price pressure there will be on tech. This is great for a business, but it could portend the next collapse in tech pricing buoyancy.

Similarly, software development as an R&D expense does the CFO no favors on the income statement. Development labor has commanded a premium price for many years now - it's been counter-cyclical since 2009, rising while labor costs in the broader economy stagnated or sank. CFOs don't have a high tolerance for this. Importing a high cost of labor onto your statement of cash flows because you're investing in an asset that you expect will generate future cash flows is one thing. Importing a high cost of labor onto your statement of cash flows for an R&D experiment is entirely another. As CFO, you're more comfortable paying a premium for labor if you see a path to getting it back; you're less comfortable if you're spending on some "ideation" boondoggle. Labor scarcity, cheap capital, easy profits, and a growth-through-tech-frenzy make boondoggles less onerous; a change in those conditions will make them far less tolerable.

The prevailing business conditions are changing, bringing capitalization back with them. Or, at least, tech is being asked to bring capitalization back. Tech is less well prepared to answer: while tech has evolved beyond fixed assets in data centers and long-cycle Waterfall delivery, it never truly matured how it accounts for its costs in the context of the host or consuming business. If anything, it's thumbed its nose at finance, allowing labor scarcity to afford it the freedom to drive itself more toward a no-strings-attached expense.

If the capital cycle still matters, this is bad for tech. If the tech cycle trumps the capital cycle, it doesn't. We'll look into that a bit more closely next month.

Capital Structures and Organizational Pathologies: Tech Investments in Slow Growth Equity Funded Companies

The volatile nature of tech companies makes them better suited to equity funding as opposed to debt. Equity is high-risk capital: owners are exposed to the upside of growth (you stand to make a lot of money), but also the downside of failure (you stand to lose everything you put in). Debt is not: how much risk is there to the lender when the borrower guarantees a return? Plus, in the event of a liquidation, creditors are first in line to be made whole.

Of course, there is risk with debt finance: if the borrower gets in trouble and has difficulty servicing the debt, the value of the debt falls. And there is high-risk debt: junk debt gives high-risk borrowers access to debt finance and debt investors more risk exposure than debt usually permits. Also, tech companies that become utilities - think Oracle or Microsoft - do lend themselves to debt finance. But that's because they are utilities more akin to electricity and water than volatile, shoot-for-the-moon tech firms. We don't equate investing in Microsoft with investing in King Digital Entertainment.

On the whole, tech investors want exposure to runaway upside, not steady returns. We get this exposure through equity capital.

Portrait of a slow-growth (non-technology) firm. Less than 10% of it's Enterprise Value is debt. It has a strong market share position and slow annual growth that allows it to pay a slightly increasing dividend year on year. As technology starts to become more prominent in their industry, they appear to be well prepared to take it on.

But are they?

This is a firm under no real pressure. Because it doesn't have a credit rating to support, this firm will be sloppy in operations. Being slow growth, they'll feel no threats to revenue, and likely can't conceive of any, possibly even believing they are uniquely immune to competitive threats. Mollifying investors every year with a slightly increasing dividend will attract capital satisfied with steady returns, not agitating for growth.

Their strong market position and simple balance sheet will give them the patina of being a "tech ready" firm, positioned to be leaders of tech innovation that can further improve their grip on the market. The board might go so far as to insist on the CIO bringing tech investments up for consideration, and the CEO may bring attention to these during earnings calls.

But the culture is fundamentally risk averse: why mess with the good thing we have going? Bloat in their cost of operations will crowd out cash for investment. The nature of tech investing - burning through a lot of cash on development and marketing to grow a user base - will be unpalatable. What they have in the appearance of readiness to be tech investors quickly evaporates in the lack of will to follow through.

Which is not to say they don't invest in tech, but it is a "me, too" firm that invests in low-risk technologies in response to what competitors have done. It is not an industry disrupter looking to change the competitive landscape through tech. They'll see investments in tech that drive a bit more efficiency out of their existing way of doing things (such as manufacturing or supply chain technology) far easier to conceptualize and pursue than high-risk, exploratory investments or acquisitions.

It might seem that new leadership or a few quarters of revenue contraction could break the company out of its slumber. But for fundamental change to happen, a CEO has to sell the board on a vision for how the competitive landscape is changing and what the company needs to do to lead it; cut overheads and perks; get line managers to tighten operations; and convince shareholders that the money saved is best redirected toward the pursuit of the new vision. And that's just the start: follow-through execution to make the vision a reality requires a change in the culture.

Changing the culture from "coast" to "hustle" challenges the company's willingness to act, all the way to the board. Sadly, if the stock price gets a lift simply by basking in the reflected glory of actual tech innovators, the board is more likely to interpret it as a validation of its decisions to date than it is willing to depart from them. The firm may be tech ready, but it is change averse.

Capital Structures and Organizational Pathologies: Tech Investments in Debt-Fuelled Capital Intensive Companies

Portrait of a growing company: a corporate parent with two-thirds of its enterprise value in debt, running two separate but interdependent divisions: a capital intensive asset heavy business, and a cash generative consumer-focused operating firm.

If you're the CFO, your primary concern is the debt capital that's financing your growth. You want to keep your credit rating strong to minimize the cost of rolling over debt (to finance existing assets) and the cost of raising new debt (to fund expansion). Every extra dollar paid to service the debt is a dollar less yield the business generates for its own use.

The CFO keeps the credit rating strong by having consistently strong cash flow from operations.  Even if it doesn't generate enough cash flow to cover investing activities, strong and consistent cash flows show financial discipline in running the business, and potential for financial reward at greater scale; this encourages more investment and suggests only modest risk.

The two divisions have decidedly different cash needs.  The asset-heavy business consumes capital, while the asset-light operating company generates it.  There isn't much you can do to squeeze operating cash flow efficiency from the asset-heavy business, aside from minimizing overhead costs associated with investing activity.  But you can squeeze the operating company for efficiencies, reducing total labor costs with things such as customer self-service.  The more cash hungry the asset-heavy business is for investment, the more ruthless the operating business will be squeezed for efficiencies.

The P&L is also a source of trouble for the CFO. The expanding asset-heavy division will have more expenses than income.  It isn't a problem for a growing business to post losses, but the volatility of investing activity in the asset-heavy side of the business will put downward pressure on the credit rating.  That will lead the CFO to be creative with the income statement, through things like capitalization.

What does all of this have to do with software?  The asset-heavy division isn't going to be very software intensive.  The operating company is, though.  Suppose that the operating company is in a firefight for market share, where the primary weapons are customer-facing technology (as is happening in retail, entertainment, and, to a lesser extent, airlines - all of which have capital intensive asset-cos side-by-side with cash generative op-cos.).  With labor demand outpacing supply in tech, engineers and designers are expensive. They have to be compensated in cash, since the capital structure makes it difficult to compensate them in equity.  Plus, not being an engineering firm, the company will be slugging it out to find and retain qualified engineers.  From the CFO's point of view, software development - just some part of the operating company - has a spiraling cost of labor, and it's high-maintenance (e.g., requires a lot of care and attention to get and keep people) to boot.

This is where the "we have a software company within" myth starts to fall apart.

The economics of running a competive software business don't matter a damn to a CFO who is trying to sweat every penny out of an operating company.  True, having the patina of a tech business could juice the valuation, but only in terms of the equity, not the debt - primarily because tech firms just aren't financed with debt.  If you're going to debt markets, you need financial operating cred more than you need to show tech characteristics.  Plus, the growth that mollifies the credit raters enough to turn a blind eye to the saggy P&L will have been priced into the equity; in an asset-heavy business, tech will be priced in as a necessary cost of the operating company, not as an option call on the potential for explosive growth.

Another way to look at it is, any increase in the equity value that results from the appearance of being a budding tech business is a nice-to-have for management (who have equity & options). Otherwise, with such a large debt overhang, any tech patina isn't likely to have any real economic value, e.g., the creation of an inflated currency (the company's own stock) with which it can favorably engage as an acquirer of other companies.

The opco may need tech to be competitive, but that won't be the first priority.  No matter how important tech may be, financing the debt will always trump it.  For the CFO, the priority is cost discipline.  In execution, the CFO will keep tech leadership on a short budgetary leash, forcing it to choose between hiring a lot of people but not paying competitive wages / contractor costs (and, on average, have a lower skilled engineering staff), or hiring / contracting at market rates but not being able to hire nearly the number of engineers it needs.  Either way, software development is starved for investment, crowded out by the demands of debt finance.

Accounting treatment of the software will also have its effect.  Its penchant for large capital investments on the asset-heavy side of the house will lead the company to make large capital investments in software.  Because the CFO capitalizes software development costs, the company can't afford for those investments to fail, because a failure requires the entire cost to be written off in the current accounting period, which puts a dent in the P&L.  This means that the company isn't predisposed to R&D through software (making a lot of little, experimental investments); it's predisposed to making large, debt-fueled asset acquisitions and making good on the convenants that go along with them.  In practice, the company will inject more capital into distressed software projects rather than let them fail.

The portrait of a growing, debt-fueled, capital intensive business is the antithesis of a modern software company.  Software companies are high-risk businesses: investors wager that the people in the firm can not only create interesting technologies, but can find users for them, and ways to monetize them.  The predictability and stability demanded by debt service obligations don't give rise to innovation and disruption; they create stagnation and sclerosis.  That puts paid to any suggestion that a debt-fueled, capital intensive business is really a software company in disguise.

Next month, we'll look at other operating pathologies driven by the capital structure.

Without the Right Capital Structure, There is no Software Company Within

Is every company destined to be a software company? From a production perspective, there's reason to believe so: relatively minor things that were once the domain of hardware (configuration set by switches on a circuit board), operations (merchandise re-ordering based on sales and quantities) or subscription (license fees paid for usage) have become things that are now the domain of software (configuration is set through a browser interacting with Java code running in a Linux variant deployed on a hardware device; algorithms that automatically re-order merchandise based on seasonal, demand & promotional variables; advertising-sponsored or use-metered interaction). Virtual data centers, real-time algorithmic pricing, and new media are simply larger versions of that same phenomenon.

Production isn't what it used to be. A century ago, production was king: demand outstripped supply in economies with emerging consumer classes, which gave power to producers. That has long since changed. Today, production has few sustainable advantages: it is over-built (e.g., automakers have far more capacity than demand), highly flexible (lower labor intensity and cheap capital means production can shift quickly in response to economic or political demands, but by extension means there is no intrinsic strength derived from a "highly skilled labor force"), and subject to constant innovation in inputs (look at the progress in materials science in the last two decades). Producers can only counteract deflationary forces at their core with ruthless cost control and brand allure. A producer does this with a combination of efficiency (squeeze every penny from raw materials sourcing to distribution) and by appealing to or outright fueling user vanity (engender customer identity in every facet of its business).

Software is the means through which both of these things are done: we can use software to gather data, analyze performance and adjust operations in near real-time; we can also use software to reinforce identity, influence attitudes and drive behavior of consumers. No software, no chance.

So producers have to become software companies. But what does that mean exactly?

To somebody running a business, it means realigning internal operations. We have to look at skills and capabilities: we're not going to be much of a software company if we don't employ any software engineers. There are process and cultural considerations, too: an "optimized" business might squeeze more performance out of operations through software, but is less likely to be capable of capitalizing on external data that allows it to "re-invent" its industry through software.

But skills, capabilities, processes and culture all wilt in the face of an overbearing capital structure. A company financed to produce long-term stable cash flows from operations isn't a company that is prepared to respond to threat of competitive innovation via software or anything else, let alone one that will be a source of competitive disruption. It might consume a lot of software. It might even create a lot of that software. But software intensity in what we do doesn't make us a software company, any differently than walking for miles every day makes us athletic. Operations and execution matter to the bottom line, but ultimately dance to the tune called by finance.

Next month, we'll look at the organizational pathologies created by different capital structures and how those make a firm that innovates and competes through software as opposed to a firm that ingests and consumes software.

Would Uber be so intriguing if we thought of it as the next American Airlines?

Suppose for a minute that self-driving cars become commercially available. Obviously, a lot has to happen before we get to that point, but suppose that it does. What happens to the economics of ground transportation?

Today, cars are owned or leased by individuals (households) or fleet operators (delivery firms or rental car companies). Auto manufacturers sell to dealers, who sell to individuals and firms; finance companies from universal banks to specialist lenders finance the trade. The buyer trades cash for utility (you have the car that suits your lifestyle), convenience (you have the car that you want any time you want it), and vanity (your car is a projection of who you want people to think you are). The rise in popularity of leasing hasn't changed things all that much because lessees make payments in exchange for possession that guarantees the same utility, convenience and vanity enjoyed by an owner-operator. Because there are millions of owners (and lessees), ownership is fragmented. Fleet operators have some buying power, but large fleets don't represent a very big portion of the total auto market.

Cars are underutilized: the average car sits unused about 95% of the time. This creates an opportunity to squeeze more efficiency out of the fleet. Enter firms such as Uber and Lyft: an idle person can take their idle car and give someone a ride. Of course, it isn't the car that's being shared, it's the labor: an UberX customer rents the driver, not the car. Uber brings new sources of labor into the market for personal transportation (competing against car ownership, car rental, taxi, limo, etc.), makes it conveniently accessible to passengers, and algorithmically optimizes pricing (the financially lucrative if socially unpalatable "surge pricing"). In a labor-intensive market prone to chronic shortages at the point of consumption (there never is a taxi when you need one in Manhattan...), this gives Uber and Lyft a price advantage over incumbents and attractive growth potential.

Enter the self-driving car. Suppose that we get autonomous self-driving cars that don't require a human operator backup. A self-driving car could deliver itself to a consumer and return itself to a vehicle pool. A vehicle that arrives when it's needed, and disappears when it isn't, changes vehicle consumption into an on-demand, short duration rental transaction. Companies that operate fleets of cars will initially compete on algorithms that maximize fleet utilization, plus inventory management that optimizes the mix of vehicles available in specific geographies at specific times (fuel efficient sedans for trips from home to the airport on weekdays, and light trucks for weekend DIY projects). The more efficient the dispatch and the more comprehensive the fleet, the easier it is for an on-demand service to satisfy an individual's need for utility, convenience and vanity in their choice of transportation.

In a world of self-driving cars, however, the service operator isn't optimizing labor, it's optimizing asset utilization. The economics of ground transportation will change to reflect this. A self driving car changes the current owner-operator (that is, the individual driver) into an on-demand renter-passenger. Rental transactions become simple debit or credit transactions between an individual and a fleet operator.

In this world, the users aren't the owners, but neither are the operators. Auto transportation will come to resemble the air travel business, where there are companies that own fleets of airplanes and rent them to companies that operate them to deliver passengers and packages. The fleet owners - firms like International Lease Finance - are asset-heavy companies that buy and insure aircraft from manufacturers (Boeing, Bombardier, Airbus) and lease them to airlines who operate them to deliver people and parcels. Being large buyers and large suppliers, the lessors concentrate ownership of the assets, which gives them negotiating power with both manufacturers and lessees. They are finance firms that throw off fixed-income-like returns to their investors.

The fleet operators are asset-light, leasing the aircraft (an operating expense) and slugging it out with one another for consumer market share. They throw off equity-like returns because they follow the ups and downs of the consumer economic cycle, facing the simple economic threats of substitution (videoconferencing has culled some demand for in-person meetings) and competition from start-ups siphoning off revenue of the most profitable routes (it isn't hard to start an airline, but it is hard to make money at it for any sustainable period of time, as the list of defunct carriers attests. It will be no less difficult to start an auto operating business).

The auto fleet operator - now an "asset sharing" company of assets it doesn't own, but rents - cannot compete for long solely on efficient dispatching and high asset utilization. Being operating companies of utility services, they compete on price, so they need to be merciless about increasing operating revenues and decreasing operating costs. They will develop complex pricing structures, just as airlines have done to charge premiums for better seats and extra bags. They will segment their market into a small premium segment that rents luxury vehicles and a mass segment that rents more humble rides. They will develop loyalty programs that rewards individuals for transaction volume and revenue contribution. And although it's tempting to think about fuel consumption as an individual responsibility as it is in the owner-operator model, the fleet operator will quickly realize that energy is a major cost component, and will hedge fuel costs as a way to lower their operating cost - or be able to offer lower operating prices vis-a-vis competitors.

We have cars that can drive themselves today. But a lot has to change before a significant number of the cars on the road drive themselves - and not just because of the equipment, infrastructure and policy needed to make it happen. Cars are vanity purchases. Suburban transportation and lifestyles are bound to automobiles. The convenience factor, particularly in periods of high demand, will compel many to continue to own or lease. The individual ownership or lessee model won't change any time soon, so this future is still a long way out.

Still, it suggests that the future of the dial-a-car business will be an exciting one, but for a different set of reasons than anybody is projecting today: intense competition, race-to-the-bottom pricing, volatile earnings, and the occasional trip through bankruptcy. Not exactly the kind of future that captures the imagination.

Matrix IT Organizations, Part II: The Inmates Are Running the Asylum

A few months ago, we took a look at the pathologies of matrixed organizations: no focus, amateur management, and people waging turf wars to secure power that they can exercise without consequence. The result is stationary organizational inertia, the portrait of a seized-up business.

When non-executives enjoy power without responsibility, the corollary is that executives suffer responsibility without power. The organisation cannot pursue a consistent or coherent strategy, and may find it difficult to take any decisions at all.

-- John Kay, How a proud corporate history can lead to poor governance

Matrices empower petty bosses but disenfranchise organizational leaders. The owner of a product P&L doesn't "own" the people who produce it: executors report to managers in other parts of the organization, are shared with other teams, and may be so over-subscribed they have little time to devote to any one of them. Non-technical product leaders will struggle to navigate business goals to completion through the sea of technical tasks their teams force them to sail in. Knowing their skills and institutional knowledge are in short supply, individual executors and their supervisors get to pick and choose what they work on. The product leader ends up negotiating in all directions - with the people nominally on their team, those people's managers, and their peers struggling with the same organizational dynamic - to secure the time, attention and cooperation of labor. This isn't leadership, this is perpetual pleading, often just to complete the most marginal of tasks.

The chaotic process is vigorously defended by claims of democratic legitimacy, and by reference to the traditions and distinctive values of the organisation. But the democracy is a sham, and the values and traditions [...] encourage a tendency to self-congratulation immune to deficiencies in current performance.

-- Ibid.

Although power rests with people in execution, few will derive any joy from the situation. Whether they have power or not, executors are constantly pulled in multiple directions at the same time. In an organization over-run with demands, people will resort to coping mechanisms. One is process: if they can't control demand they can control the means by which people making demands interact with them, giving them some semblance of "control" over their universe. Another is denial: as Dr. Kay points out, they've lost the ability to recognize that the business context itself is idiotic, yet will take triumph at how well they cope. To wit: revenue is declining, infrastructure is decrepit, quality is poor and we can't make even the most simple of decisions, but my goodness we are so much better at communication since we adopted Scrum. High five!

This is organizational madness, and the inmates are running the asylum.

Companies don't set out to be organized as matrices. They resort to it when revenues fail to keep pace with the costs of doing business. When they do, it suggests that the business is trying to do too many things at the same time. It also suggests that many of the things the business is trying to do don't generate much revenue. Put more simply, the business is distracted by a lot of bad ideas. This isn't a problem of organization or of operations leadership, it's an executive leadership problem twined with weak corporate governance that has failed to keep that executive on a short leash.

I once worked with a private equity-backed firm that had a portfolio of four very different digital media products in different stages of maturity, with limited cross-product synergies. Two were past their peak and in unarrestable decline, one was ex-growth, one was growing. The technology organization - including software development - was shared across all products, with tech costs subsidized by the entire business. The company was unprofitable, dependent on life support from private equity injections. To justify those, the corporate headline was growth, although they tried to make the case that there was a profitability story in some of the lines.

We calculated product-specific P&Ls. These revealed that no product was operationally profitable if it had to carry the burden of its actual tech costs. This was due to product customizations given away by sales as a way of luring in new clients to replace lost ones. The slipshod software that resulted from those freebie customizations came with high running costs; company and customer alike got what was paid for in that unfunded customization.

We also did a revenue analysis. It revealed significant client churn across the lines, and that pricing of the growth business was so anemic that it would never achieve sufficient organic growth to provide the revenue the firm expected. Worse still, this sole growing market was maturing rapidly, creating downward price pressures they could do nothing to combat.

Operations and technology were as described in this and the prior blog: unable to focus, fiefdoms without responsibility, and so forth. Being unable to put a floor under the declining businesses' revenues plus a permanent pricing impairment on the "growth" business meant operations and technology would always be starved for cash. There is no wizardry that would turn this around; it was simply a collection of bad businesses.

The sane alternative was to simplify and focus: dispose of the declining and ex-growth businesses or run them for cash; sell the growth business or acquire competitors to consolidate the industry to achieve scale; and invest in organic development of a new media property. Unfortunately, the CEO saw a portfolio of properties that had thousands of visitors and just enough revenue that he could convince the board to keep the funding taps open, because there had to be a pony in there somewhere.

The options aren't all that great in this situation, which is why professionals aren't attracted to them in the first place. If you're brought in as Chief Executive or part of an executive team with an explicit mandate from the board to make sweeping change, you have a chance. But if you have a weak board overseeing a delusional CEO and a sales force for whom every dollar of revenue is the same, all producing initiatives that require tech and operations to compromise to compensate for a lack of revenue, you're wasting your time: you're in the asylum, and there's no one to hear you scream.

Activist Investing in Strategic Software Chapter 1 Excerpt - Why Governance Matters

I've published drafts of the introduction and first 4 chapters of my book, Activist Investing in Strategic Software. I still have some citations to finalize, several visuals to integrate and a lot of editing to do. But the foundation is there. A sample of the book (currently, just the introduction) is available on from the site.

Here's an excerpt from Chapter 1, Why Governance Matters.

* * *

That there are abundant examples of bad governance but few examples of good ones comes as no surprise. What passes for "good" in governance is not all that remarkable. Boards, being the representatives of investors, are expected to be independent, diligent, and uncorruptable. Independent members of corporate boards are assumed to be people of capability and integrity. People in governance roles are expected to discharge their duties competently; meeting expectation is not exceptional. Hence we have few examples of good governance but many examples of bad.

This doesn't help us understand why governance is important.

Poor governance, such as in the cases of Olympus, Hollinger, Madoff, or the United Nation's Oil for Food program, can lead to devastating outcomes that are plain as day after the fact. Yet as we established in the prior section, there are objective characteristics of good governance: set expectations, invest authority, and validate results. And there is research to suggest that the presence of these have a significant impact on bottom-line results.

In a study of 1,500 companies by Harvard professor Paul Gompers, well governed organizations outperformed poorly governed ones by 8.5% annually. “Well governed companies face the same kind of market and competitor risks as everybody else, but the chance of an implosion … by ineffective management is way less.”

-- Gavin Anderson, Chairman, Governance Metrics International

Good governance reduces risk of bad things happening, and there is reason to believe it is a contributing factor to superior performance

Just as a corporation is an investment of capital, so, too, is strategic software. What is true for a company at a macro level should be true at a micro level. The characteristics of good corporate governance should be present in IT governance: an independent board that sets expectations, chooses and changes leadership as necessary, and validates results reported by that leadership.

Activist Investing in Strategic Software

A few years ago, I felt I had enough experience - and had put enough thought into the subject - to write a book on governance in software development. I had observed that most tech firms and captive IT organizations are largely left to self-govern, and both are pretty light touch about it. I had also observed that governance is widely misunderstood and the term is used in technology in a lot of different ways, almost universally incorrectly. With more ambitious investments being made in software and the success rate of large projects not getting all that much better, the need for better governance was there. Plus, it seemed to me that if IT didn't get its act together soon enough, the CFOs of the world were going to get IT's act together for it, so it also made sense to write it from a bit more of a financial rather than an operations perspective.

The timing was good, too, because the prior decade had given us some very well documented examples of egregiously bad corporate governance, ranging from isolated cases of accounting fraud (Worldcom and Parmalat) to the near-collapse of the banking industry that resulted from so many firms taking too much risk onto their balance sheets, their boards having absolutely no idea they had done so. There was some nascent research suggesting that good governance has a measurably positive impact on business outcomes, and also that "activist investors" - people who force their way onto the board of a company to agitate for change - were by and large net positive to a business. All together, we had great examples of how not to govern as well as behaviors we could use as a standard to define what governance really means - practiced or otherwise - in software development.

Within a couple of years, I had written enough material to compose a draft. Then I took a hiatus from it.

In the years since I wrote the first draft, a tension has developed between advocates of "innovation" and champions of "scale" in software development. In one corner are the enterprise development people who say control over operations yields predictable results. In the other are the lean startup people who say that discipline in execution twined with feedback loops is control enough, so just let people go on voyages of discovery and you'll have far better business results. The control camp claims that innovation is possible in their way because it embraces Agile (evidently, all you need are "innovation sprints"). The lean camp claims they can scale to the size of a large business (which may be true, but they're light on practical details). Both say they can revolutionize business itself.

But both camps take an execution (that is, operations) perspective. Execution is important, but if we're going to make organizational impact, we have to do it from a financial, not an operational, perspective. Operations are cost. Investments are value. To change the business of software, we have to speak the language and act the part of the latter. It doesn't matter how revolutionary or how beneficial a different way of delivering software can be to a company: nothing that comes out of either camp is going to cause the authors of Fundamental Accounting Principles to overhaul their text.

I am once again writing the book. I will publish it iteratively. It is still early days - no cover art, not much of a landing page.

But today, the first draft of the first chapters of my book, Activist Investing in Strategic Software, is available on Leanpub.

Matrix IT Organizations, Part I: Turtles all the way Down

Multiple layers of authority overlap both horizontally (different people and committees engage with the same issue) and vertically (many decisions are liable to review by some other body). The lack of focus in decision making results in an absence of executive authority; while professional management is subject to random amateur interference. In consequence, able people are not easily attracted to management roles; and so the amateurs view the professionals with often justified and frequently reciprocated contempt.

-- John Kay, How a proud corporate history can lead to poor governance

A business has many sub-organizations. They may be functional (sales, accounting, etc.) or regional (EMEA, Americas, etc.), or specialized (e.g., product). A company may consist of all three: regional sales and marketing teams, working with multiple product teams, all of whom share corporate-level finance and legal. We want the organization structure to balance customer service with operating efficiency: completely autonomous divisions offer high customer service at a cost to our customers or to our profitability, while completely silo'd organizations squeeze every penny of efficiency at a cost to customer service. Competitive customer service at the lowest cost of execution lies somewhere in between these extremes.

Captive IT faces the same challenge as the rest of the business: organize to provide the greatest level of service while containing costs. IT generally organizes around technical roles: we have infrastructure people, database people, helpdesk people, software development people, and so forth. We also have specializations therein: we have ERP developers, who are not the same as our front-end developers, who are not the same as our legacy system developers. And none of them are quite the same as our QA people.

These sub-specializations are fairly well entrenched because career path is generally associated with role, and even specific technologies. For one thing, deeper expertise in a narrow set of technologies will command a higher salary than shallow expertise in a wide range of technologies. For another, a manager is unlikely to promote a promising member of the web development team to be tech lead of an ERP team because the technical knowledge is not transferable.

IT leaders structure their organizational hierarchy with this in mind. For utility functions, this works just fine: provisioning hardware and e-mail accounts is the same no matter who the user is. But in strategic software development, the business domain influences technical implementation, so IT needs tighter alignment with the business. The specialist IT structure is mapped to more granular business customers in a matrix: we form delivery teams to support a business line or a specific product owned by the business, but each team's tech lead reports to a VP of engineering within the tech organization.

Like everybody else, IT is under cost pressure. The greater the pressure, the more likely IT leadership is to make something into a shared service, which translates into fewer people owning multiple responsibilities for multiple teams. Quality assurance, project management, and techops, for example, can provide greater service when paired with a business partner, but become organizations unto themselves (with fewer staff) as a means of creating cost efficiencies.¹

From an organizational perspective, this makes things somewhat untidy within IT because we have a matrix (shared services) within a matrix (development teams organized by business line, but reporting up to an engineering leader). If there is a shared service within a shared service, such as DBAs being part of techops, we have a matrix within a matrix within a matrix. It's turtles, all the way down.

Add to this the recent phenomenon of product organizations. A product hierarchy - common but by no means exclusive to tech firms - is chartered to elevate users (people who use the software) and customers (those who pay the bills for those who use the software) in ways that subject matter experts and software engineers are not able to. As the proxy for consumers and buyers, they influence priorities and packages of functionality. But product owners don't necessarily have strong footing in either the business domain or software development. In practice, they act as a referee between SMEs and engineers. At best they're an emerging function clawing at opportunity from a different perspective; at worst they're another level of intermediation in the decision making process.

And so we have the situation described above by John Kay: no small number of people being brought to bear on a problem, but a structural inability to get results.

With no defined power structure, the vacuum is filled by people who turn non-executive roles into a near full-time occupation. [...] Petty politicians enjoy the feeling of being at the centre and jostle for power; the power they seek is not the ability to get things done but the negative power that comes from “no decision without me”. Secrecy about matters of no significance bolsters their sense of self-importance.

-- Ibid.

Instead of better business alignment, we have fragmented ownership and competing priorities and agendas. Matrices create, rather than alleviate, impediments to getting things done.

In Part II, we'll look at executive disenfranchisement in the matrix organization.

 

¹ It's worth noting that the decision to make something a shared service is frequently justified as a means of promoting "best practices". Functions like QA or devops that are fragmented into separate product teams will show inconsistent performance; consolidating them into a single function should, in theory, be a step toward making them more consistent (ignorant of technical, asset or personnel restrictions on that). The irony is that somehow, "best practices" - whatever that's supposed to mean - will compensate for the fact that a critical function is deliberately being starved of investment.

The CIO and M&A, Part II

Integrating businesses is no small task.  Established workflows, systems and tools are vigorously defended yet poorly understood.  Fearing for their jobs, people will equate systemic knowledge with job security.  Many in the acquired business will cling to their legacy identity. Organizational politics - and power plays - will alter tactical integration plans.  But it is the business goals that investors signed up for - not the internal special interests - that will determine the fate of the leadership responsible for the integration.  How do we stay focused on these?

Be a business leader, not a technology partner. Technology leadership must be fluent in the broader business context of the integration and be prepared to make decisions on behalf of the business, not just the technology applied to the business.  This means being or bringing in business process analysts to simplify the operations - and with it, the technology - of the business itself.

I wrote last month that most material on the role of IT in M&A are platitudes, and this certainly smacks of one.  But the fact is, this is not something that IT departments have in recent years positioned themselves to do.  The change in moniker from "Information Systems" to "Information Technology" has been a detriment to CIOs: the word "systems" implied responsibilities inclusive of business and technology, whereas the word "technology" suggests it is solely responsible for tech.  As a result, there is less expectation that tech will shape business decisions as much as it will carry them out.  It doesn't help that business analysis skills remain low in captive IT.

M&A gifts captive IT with the opportunity to be the "resident adult" in sorting out intransigent participants in an integration. However, that opportunity exists only if it is prepared to act as a business leader and not merely a technology supplier.

Slowly strangle, don't wholesale replace. Existing systems are complex: they have highly specialized rules that were developed over a number of years, they were developed with very different architectural principles than would be applied today, and the older the underlying technology the scarcer the technological know-how there is to incrementally change them.  This makes it easy to make the case that dueling systems are incompatible with one another, are no less valuable owing to the criticality of the specific edge cases they accommodate, and can only be replaced through a large "enterprise"-scale rewrite.  Thus we have no choice but to maintain the status quo, and only costly and high-risk change can possibly sweep it away.

The headwinds to change blow fiercely; there are always plenty of reasons not to do something.

Unless both organizations have extraordinarily geriatric technology, proposing an enterprise refit will be met with skepticism in the boardroom that will cast doubt on our leadership capability.  Even a big-bang retrofit of one incumbant technology to take the place of another will receive only a grudging endorsement.  Both scenarios also create tactical confusion: should existing systems be modified to meet immediate business needs or do we wait for the big-bang replacement?  And what do we do if that big bang replacment gets delayed?

We avoid this trap by strangling existing software.  In effect, we allow our portfolio of assets to continue to evolve with the business while simultaneously deprecating and retiring them.  We do this gradually, identifying specific functionality that can be integrated and replaced.  We have the practices and technologies today - from continuous integration to feature toggles to branch by abstraction - to make this a matter of will.  It is also palatable to the board because it gives us a means to show how we are structurally reducing our cost of operations in a manner that will support the business in the short-term and sustain it in the long-term, not a slash-and-burn approach that makes it thinner at the cost of making it more sclerotic.

This will mean making some unpleasant decisions. We may have to create new code - a lot of new code - to integrate old code on our way to fully retiring it.  We may have to integrate in unpalatable ways (e.g,. at the database level) where legacy systems do not support modern architectural principles.  And there will be times when the extent of integration will makes our collection of assets very complicated.  This means that our measure of success isn't just getting things deployed, but getting things removed.  To the CIO, the critical measure is a composite "simplicity index" of all IT systems, not "integration progress" in simply making systems work together.

Insist on excellence in engineering.  When the clock is ticking, there will be temptation and pressure to cut corners.  We can create the appearance of integration with quick and dirty solutions, and all that matters in the end is that it works, not how it works.

The phrase "we'll fix it later" probably has the lowest conversion rate of any statement made in business. An implcit expectation in M&A is that we are investing in simplicity and robustness, not complexity and brittleness.  The reality is, we're not going to get money later to pay down technical or operational debt we take on. If the combined landscape has more moving parts and fragmented institutional knowledge than the sum of the parts of the combining companies, we'll have a higher cost of operations and, therefore, have failed.

Investigate, measure, and draw attention to quality of engineering.  Instrument all code, looking specifically for complexity, duplication, testability, and test coverage.  Incentivise good engineering practices and reward teams that make structural and procedural improvements.  Take deliberate action against poor engineering decisions: delay an implementation rather than accept a poor one.  We have to live with the consequences of our decisions; make clear that we have invioable standards of performance.

Nobody is irreplaceable.  Inheriting somebody else's code is never much fun.  We have to deconstruct what other people were thinking at the time they created it, while simultaneously trying to understand the business context that existed at that time versus the context that exists today.  It's much easier to fight for funds to perpetuate a legacy team than it is to take responsibility for cleaning it up.

Two things to remember: it's just code, and the people behind both the code and the business usually don't have as much systemic or contextual knowledge as we project into them that they have.

To the first point, most code is not as algorithmically complex as we are told that it is.  The implementation might be complex, but implementation decisions are generally easy to discern (somebody really liked Java interfaces, so everything is implemented as an interface).  Once we figure that out, it's fairly straightforward to restructure the code and increase test coverage to make it more testable.  This is true for current and legacy languages alike.

To the second point, don't assume that the business leaders have as solid a grip as you'd hope they do as to why they do the things they do.  Some years ago, I was working with a firm to redesign fleet maintenance operations.  The existing suite of software tools were a combination of RPG, Visual Basic, Java and Excel, tied together with a number of manual integration steps.  The business operations leaders could only understand operations in the context that the technology allowed them to do these things.  We had to understand their business operations better than they did to get them to understand the actual value stream.

Do not be held hostage by tribal knowledge or the perception of that tribal knowledge.  Reward people for knowledge sharing and provide career paths for people to move beyond system caretakers to leadership roles that builds on their experience in mission-critical systems and knowledge of how the business itself operates.  Do not be afraid to cut people loose who are obstacles to change, no matter how entrenched they are perceived to be. Best of all, replacing legacy systems will reduce pockets of that knowledge: we start the clock ticking on it the minute we start to retire it.

Put your personal credibility on the line for these things.  A CIO has only as much time as the M&A horizon to create a common culture within the technology organization. Whatever the cultural norms are of the two firms at the start, insisting on engineering excellence, business leadership, and gradual improvement while being willing to accept responsibility for cutting loose tribal knowledge sets a decisive tone of change within an organization.  This creates both a new mission and a new identity for everybody.

Most importantly, we have to make it clear to all and sundry that we are every bit as much on the line for these things as they are.  We will take responsibility for a delay in implementation where quality is sub-standard.  We will develop new leaders in our organization rather than being forced to retain people in existing roles.  Our actions will speak louder than our words.

Nobody is irreplaceable.  If we fail to deliver, we'll find that out to be true for us, too.

The CIO and M&A, Part I

"It is hard not to be cynical about this. M&A is a great process for creating fees for bankers, and for destroying the value held by shareholders."

-- John Authers, writing in the Financial Times

Industries tend to go through waves of deal-making. Sometimes it is divestiture or separation: sprawling firms that serve different buyers or markets don't achieve much in the way of operating efficiency, and a "conglomerate discount" priced into their equity means there is value that can be released by dividing a firm into multiple businesses. This is something H-P did in the late 1990s, and is about to do again. But usually, deals are acquisitions: competitors merge to gain more power over costs and prices (United Airlines merging with Continental); large firms acquire smaller ones to enhance their core (Yahoo has been on an acquisition tear in recent years), diversify their markets, or simply to prevent a firm from falling into the hands of competitors (Microsoft's acquisition of Skype).

The justification for a merger or acquisition usually involves some quantification of synergistic benefit: the two businesses have so much in common they can achieve greater profitability together far sooner than they would be able to on their own. This can be achieved through sales: Company A and Company B sell complimentary products to the same buyers; a merger of the two would allow for cross selling, resulting in larger and more lucrative sales. It can also be achieved through operating efficiencies: Company A and Company B can operate just as effectively with, say, 70% or less of their combined procurement, finance, accounting, HR and IT organizations.

The expected synergistic benefits to revenue and costs are calculated, then taxed and capitalized, to come up with a hard economic value to doing a deal. This makes them important to the CEOs involved because they help them sell their respective boards - and shareholders - on doing a deal. Their importance increases in direct proportion to the premium an acquirer is willing to pay to buy another firm. Synergies can be substantial: the proposed synergies of the merger between Office Max and Office Depot exceeded the combined market capitalization of the two firms.

* * *

"Most deals fail to create value because the buyer paid too much, or because the acquirer failed in the difficult task of sticking two companies together. Glossy proclamations of new strategic visions often boil down to a prosaic cost-cutting exercise, or into a failure of implementation."

IT is at the center of deal synergy. Obviously, we don't want to pay to maintain multiple e-Commerce sites or pay licensing fees for multiple ERP systems. But redundant IT systems can increase the cost of doing business: if we need people in finance to write custom reports to combine financial reporting across the two businesses, the merger has increased our total cost of operations. We need to combine systems, and do so quickly.

There are plenty of cookie-cutter frameworks for combining businesses, even their technology systems and operations. This also means there are plenty of platitudes to go round: "Involve the CIO as part of the executive team from the start" and "IT doesn't work in isolation". True, but not very helpful. Rubber hits the road in M&A in the actual combination - and reduction - of systems. Platitudes will not change an ugly operating reality.

IT in M&A can be a very messy business. For example, suppose Company A acquires Company B and intends to move Company B - running a highly customized & partially proprietary ERP - over to Company A's similarly customized, but commercial-off-the-shelf, ERP system. Company B has very different business processes and communication channels from Company A. The new divisional leader for that part of the combined company is from Company B and decides he wants those processes applied to the combined business. IT must now make changes to Company A's ERP system and dependent code to accommodate this change, in addition to migrating data. Costs just went up and the consolidation timeline just got longer - and depending on your point of view, it looks like an IT problem.

This also applies to the mundane stuff. For example, IT learns that the data and data structures in Company B don't exactly line up with Company A, so data migration is going to take more effort than originally expected. IT responds by creating data warehouses to house consolidated data so that Finance can run its consolidated reports. Costs just went up, as did operational complexity: those warehouses - and the ETL that refreshes them - have to be maintained and updated.

When companies pay a premium to fair value of net assets for a business they acquire, the excess is recorded on the balance sheet as goodwill. In theory, the value of the combined business should increase as synergies are realized, obviating the need for goodwill. The reality - and core to Mr. Auther's comments above - is that companies have a tendency to pay too much in acquisitions and end up taking a writedown. One study found that between 2003 and 2009, some 4,600 firms wrote-down goodwill due to impairment, amounting to 20% of total recorded goodwill. The study went on to report that there are some serious ramifications to this. For one thing, "the news of goodwill write-off [...] precede[s] CEO resignation and can trigger shareholder lawsuit." For another, "Firms with goodwill write-offs significantly under-perform in future." (Feng Gu, Goodwill and Goodwill Write-off: Economic and Accounting Implications)

So, in a M&A situation, there's a lot on the line for the CIO: you don't want to be the reason the boss loses his job, and you don't want to be a reason why the stock price underperforms. But your operating reality is messy: you're beholden to tribal knowledge of systems you've inherited through the acquisition, you're at the mercy of business decisions that are made for local optimization or simply local convenience, and you're under the gun to enable finance and accounting to create the patina of a combined business for the benefit of the people who approved the deal. As CIO, you'll be under pressure to extend and even bump your payroll to prevent loss of knowledge, create teams to chase business decisions with new software, and take on technical and operational debt to make good on immediate needs.

There is no playbook for this.

Next month, we'll look at how a CIO can square this circle.