I consult, write, and speak on running better technology businesses (tech firms and IT captives) and the things that make it possible: good governance behaviors (activist investing in IT), what matters most (results, not effort), how we organize (restructure from the technologically abstract to the business concrete), how we execute and manage (replacing industrial with professional), how we plan (debunking the myth of control), and how we pay the bills (capital-intensive financing and budgeting in an agile world). I am increasingly interested in robustness over optimization.

I work for ThoughtWorks, the global leader in software delivery and consulting.

Friday, July 31, 2020

The Innovator's Cunundrum

Even as the pandemic hits sales, [automakers] need to pour vast sums into developing electrical vehicles - with absolutely no guarantee of success.

-- FT Lex, July 29, 2020

Socioeconomic systems in transition are impossible to navigate. At the same time that the old order is in collapse, the keys to the new order are very difficult to forge. Plenty of people bet and lost - in many cases quite tragically - during the 1918 Russian revolution, the great depression that began in 1929, the 2008 financial crisis, as well as in many other transitions in between. It is easy to realize that things are changing, but what they are changing from is easier to identify than what it is they are changing into.

Let's consider a specific case. For about a decade now, governments round the world have mandated that automobiles change from hydrocarbon-powered internal combustion engines to battery-powered electric motors. Yet the availability of electronic vehicles for sale has far outstripped the demand for the vehicles themselves. Plenty of automakers are building EVs at volume. Unfortunately, that volume is staying on manufacturer and dealer balance sheets, because legacy automakers are designing and building EVs that few want to buy.

The future is right in front of every legacy automaker, yet the legacy automakers don't really know how to crack the nut. Build EVs, check. And build EVs they have. Unfortunately, it's hard to make money on a product when the unit volume is measured in 4 or low-5 digit range. In 2019, Chevrolet sold 4,915 Volts and 16,313 Bolts in the United States, for a combined sales volume of 21,228 EVs. That same year, Chevy sold:

If at first you don't succeed, try, try again. That sounds easy enough for the legacy automakers to do: keep funneling cash flows from the lucrative legacy business of internal combustion trucks to finance more R&D of EV products (including, of course, an electronic pickup truck) until they get it right. Regulators have spelled out the future, and neither the debt burden nor equity holder's appetite for dividends preclude a healthy R&D spend. Tesla figured it out from scratch. How hard can it be?

Tesla the automotive company (ignoring the solar panel company) has (in that context) one mission - to make money manufacturing, marketing, selling and servicing a line of electronic transportation products. Sole mission and sole purpose make a clear investing proposition: this is an all-in wager. By way of comparison, legacy automakers have multiple missions: satiate bondholders and shareholders of a multi-line mass-transportation company. All-in wagers are not so appealing to investors in legacy firms.

This is especially true since it isn't clear just how quickly the clock is ticking on this transformation. EVs are the future, but when is that future? Proven hydrocarbon reserves are vast, demand for refined hydrocarbons (lubricants, jet fuel, automotive fuel) is down across all sectors and will remain depressed for years. Excess and untapped supply portend cheap refined petroleum product prices for a decade. Regulation could change that, but regulation is just as subordinate to economic needs as it is to environmental ones. The electronic vehicle manufacturer doesn't employ as many people (a.k.a. "voters") as the internal combustion engine vehicle business does. Cheap energy - be it electric or hydrocarbon - drives household productivity and therefore household leisure. Lots of entities stand to lose if the migration to EVs is too quick, EVs are the future, but that future might very well now be anywhere from one year to ten years out.

The standard playbook to navigate this dynamic is to do continuous market testing. The modern tech playbook would have that be done in the form of user need surveys, MVPs that gauge user interaction via instrumentation, and user satisfaction surveys, all in lock step. But if the market is in a volatile state, historical data is useless and real-time data only has value if the right filters are applied. Good luck with that.

During times of transition, there is no right policy, but there is wrong policy. The macro strategy risks are almost too obvious to point out. Bet too heavily on the future and you will lose. Cling too tightly to the past and you will lose. That's great policy, but utterly useless, unless you're JC Penny a decade ago standing at the city on the edge of forever with the ability to step back in time to alter the present. The micro strategy is where the transition is won or lost. The successful strategy will be one of muddling through.

In 1959, Dr. Charles Lundblom published a paper entitled "The Science of Muddling Through". The point was that policy change was most effective when incremental and not wholesale: evolutionary, not revolutionary. Dr. Lundblom was mocked by the intelligentsia of the day, who subscribed to the grand strategy theory that was fashionable at the time: that all outcomes could be forecast as in a chess match, that all plays could be anticipated and their outcome maximized toward a grand plan. The theory sounded great, but it assumed a static future path, muted all feedback loops, and was willingly ignorant of statistically improbable but highly significant events. Experience teaches us that the world is not so much chess as it is Calvinball. The grand strategy proved intellectually bankrupt as exhibited through its applications ranging from companies such as ICI Chemicals to the United States military prosecution of the Vietnam conflict. The prior resulted in monumental destruction of employee and shareholder value; the latter resulted in societal implosion.

Grand strategies will be all the rage in response to great challenge because they appear to have all of the answers. History teaches us that most, and likely all, will fail. In times of great transitions, Dr. Lundblom was right. Grand schemes and grand hypotheses will not win the day. Micro-level attentiveness, situational awareness, and adaptability will.

Tuesday, June 30, 2020

If there was ever a good time to be sure you have good governance, this is it

Since 2006, I've written multiple blog posts, a few articles and self-published an e-book on governing investments in strategic software. Software development is unique from most every other office-based occupation because it is the conversion of capital into intangible assets by way of human effort, at a level of effort that remains labor intensive to this day. Although other white-collar occupations such as back-office accounting can be labor intensive, their costs flow through to the income statement as SG&A rather than depreciation. Blue-collar occupations such as manufacturing labor can be capitalized (the labor that goes into building a car is a cost that is factored into finished goods inventory, which is a balance sheet phenomenon), but decades of capital investment in robotics have reduced the labor intensity of most manufacturing functions. True, many firms (particularly nascent tech firms) expense their software development labor costs; yet development is still a capital allocation function if they're spending investor capital or retained earnings rather than cash flow from operations to finance the development. Restated, software development is discretionary spend of balance sheet cash that could be directed to other investments or returned to investors.

Being an act of capital allocation, it has always struck me odd that most corporate captive IT organizations and tech firms self-govern the transformation of capital into software. In practice, software development governance is clubby, even more clubby than most corporate boards where the CEO has hand-picked the directors. For purposes of ceremony, IT governance is heavy-handed in reporting, but light touch in execution, loaded as it typically is with vendor reps with sales revenue on the line, delivery managers with bonuses on the line and business sponsors with promotions on the line. This isn't an environment where hard questions are tolerated, let alone asked. Some years ago, I was working with a regulated healthcare company replatforming its customer-facing solutions at all locations worldwide. It's target state one month after launch was to have 5 locations running the new software in parallel with legacy, processing 0.15% of corporate transactions, with another 5 locations ready for go-live the following month. In the event, the software had to be shut down after two locations were live for a few days because the new platform was dispensing client instruction incompatible with and contradictory to the healthcare products being provided. Sixty days after go-live, no locations were operating on the new platform, there was no resolution for this potentially life-endangering flaw, and therefore no path to production for the initial 2, or 5, or 10 locations, let alone any of the thousands of locations beyond that. The PMOs self-reported program status to the governance board? Green.

"We're all ok here" has been the modus operandi for IT governance for the past two decades. A lot of this is a function of the fact that despite the dot-com bust and the 2008 financial crisis, the first two decades of the 2000s have been characterized by overall global economic growth. Mid-way through 2020, we are now in a period of economic uncertainty. COVID-19 has initiated socioeconomic change that will have lasting effect on consumer behaviors, business practices and public policy. Uncertainty remains as the nature and trajectory that containment and combatitive policies to defeat the virus remain unknown. A lengthy period of containment and combat won't simply harden new business patterns such as work-from-home policies and consumer preference for take-out dining: it will unleash entirely new patterns as socioeconomic pressures build concomitant with human frustration at restrictions and seasonal change incompatible with policy relaxation.

The uncertainty factor matters because it creates new pressures for captive IT and tech firms alike to show diligence with every dollar spent. No matter the exposure to socioeconomic disruption your company now faces and balance sheet strength your company had entering into this crisis, the CEO was not and is not too keen on capital spend right now. While there are good cases to be made for investments in strategic software, particularly those that are reasonable preparations for how a society and economy function in the future, the tolerance for both wasteful allocation and misallocation is low.

Which brings us to the question of software delivery governance. If governing software delivery was hard during stable economic times, it is that much much harder during unstable economic times. Weak governance is highly vulnerable to threats old and new that cannot be swept under the rug worn threadbare by sudden economic convulsions. There are three threats worth highlighting: overspend, vendor fraud, and employee misalignment.

The first threat is little to no tolerance for overspending. I've written previously that CFOs earn their stripes on Wall Street by creating the appearance of control. Control arises from operational predictability: predictable operations create stable cash flows that finance healthy dividends and buoy the credit rating. In good times, perhaps the chief accountant was able reclassify a lot of maintenance work as capital improvement to bury that $2m IT project overrun a few years ago, and a late-year sales flourish buried that $4m overrun last year. In a sustained downturn, there's no accounting trickeration or sales windfall to come to the rescue. Not to mention, the CEO really wants to tell Wall Street that despite the economic upheaval, the company results were so good and the indicators so overwhelmingly positive, we're increasing the dividend. No CIO in their right mind will jeopardize the CEO's victory lap.

The second threat is an increase in fraud. Vendors have always exported overhead labor from their income statement to that of their customers. At a tactical level, vendor overhead employees are written into client contracts in loosely-defined roles that permit them to bill a few hours every billing cycle. Vendor direct labor rates are slightly inflated as a means of deflecting attention from the fact that vendor direct labor hours are significantly inflated. Surcharges such as "vendor administration services" - which amount to vendors charging their customers to make certain that timesheets are entered, invoices are generated and payments are collected - are added as service fees. And, of course, vendors cheerfully enter into one-way contracts to deliver CEO vanity projects of "re-imagination" and "market disruption" with no clawback clauses for results or outcomes. There is also the more pedestrian version where vendors enter into one-way contracts that create disincentive for improvement and (perversely) create incentive for perpetual failure: e.g., a vendor that charges per bug fix incident has no incentive to remediate the underlying cause, and actually has incentive to perpetuate the underlying cause.

These are all phenomenon that happen in good times, the product of lax contract administration, asymmetric knowledge of software delivery that favors the vendor over the buyer, and the starry-eyed "true north" ambitions of buyers. The boss wants to do this, we're not a software firm, procurement was told to get the deal done, and the contract gives little room for pushback, so everybody goes along for the ride. In unstable times, the pressures for vendors to inflate contracts to meet revenue targets, stave off layoffs, and sign obligation-light contracts to create flexibly tappable cash flow intensify that much more. Vendors have many more problems to try to export to their customers.

The third threat to look out for is the mismatch between individual and organizational goals. I wrote about this in 2013 in a two-part series on conflict. The phenomenon materializes as contrived complexity: obfuscated domain knowledge, jealously protected relationships, and unnecessarily complicated code are all examples of acts of individual self-preservation of employment that undermine effective governance of a strategic software investment. The board member who everyone knows is beholden to the knowledge of the governed will be played. If there is nobody with the domain knowledge, relationships, and algorithmic know-how to call bullshit on the executors, then the bullshitters will rule the day every day.

Today, governance is increasingly being put to the test, specifically at a time when governance standards have become institutionally lax and have been so for a long period of time. Governance will tighten, as described by John Maynard Keynes in his book The Great Crash of 1929:

In depression all this is reversed. Money is watched with a narrow, suspicious eye. The man who handles it is assumed to be dishonest until he proves himself otherwise. Audits are penetrating and meticulous. Commercial morality is enormously improved.

Keynes' statement that "all of this is reversed" is all well and good, but the fact is that regulators always lag the regulated, and governance is a regulatory phenomenon. By the time regulators catch up with the regulated, the damage is done to regulators' reputations for control, scrutiny and alignment. Rest assured that your successor will bask in the glory of being a more diligent investor, a more scrupulent auditor, and a more competent leader than you were.

If you prefer not to allow your career gravestone to be a platform for your successor to dance upon, what does it take to know that your governance practices are up to the task?

It's worth pointing out that you never will. Governance is something that is only evident by its absence. In addition to being intangible, there is no infallibility to governance: in practice, even the most prudent governance structures fail to detect problems, while the most lax governance structures suffer no damage from problems that do not metastasize. Governance is not a precise science. Governance is only obvious when it succeeds as a counterfactual (hindsight makes clear a crisis was intentionally avoided, such as investing in Bernie Madoff's fund in the summer of 2008) or when it fails (a fund piles in all of its money into Madeoff's fund in the summer of 2008).

That said, what should IT be doubling-down on to increase the effectiveness of its governance practices?

  1. Strengthen the cost audit function. Ask people everywhere from the accounting fraternity to the program management office to procurement to increase the scrutiny of every dollar that goes out the door for a strategic software investment, whether for badged employee payroll, vendor services, cloud services, or licensed product. The objective is to identify non-value-generative chargebacks. Either the person responsible for the charge can answer "what value did we get for this" or they cannot. The point isn't to spot administrative errors, but inexplicable costs and patterns of charges that point to budget leakage or legitimately high costs that point to accelerated budget drainage, and to do so while threat to budget can be contained.
  2. Strengthen the solution audit function. Engage a captive technical audit function or an external vendor with no connection whatsoever to a program of work to perform audits and peer reviews of tests, code, and team practices. Is the code written to a degree of simplicity that it is comprehensively testable, and easily maintainable by other developers? Can the piece-parts of the solution be tested in isolation and without an environment, or do they require expansive infrastructure and consistent data fixtures? Are there transitive dependencies that create false testing positives or negatives? Are integrations validated through contract tests before arriving in an environment? Is the team working in very narrow silos of domain knowledge or technical expertise? Are some people acting as bottlenecks? Have the number of hand-offs increased to complete requirements or fix defects? Have the number of defects increased, or has the time to resolution of them increased? Keeping a close eye on both the what and the how provides an early warning to delays in delivery or higher cost of maintenance than planned.
  3. Increase the threshold of acceptance of management status reports. In medicine, patient testing is frequently done to confirm or deny a threshold of "no evidence of disease." This involves taking a sampling of cells and subjecting them to tests to ascertain a percentage present per the statistically significant sample, and a trend of counts of samples made over time. A higher standard of acceptance is "no evidence of disease", but that's an impractical threshold as 100% testing of cells would be fatal to the patient. In strategic software investing, the lower threshold of "no evidence of failure" is a proxy of convenience to the board: if the program manager says the status is green and the summary indicators support that, the program manager has given no reason not to believe the status is green, but not reason to believe that it well and truly is. Program governance must raise the threshold on program management to provide "evidence of no failure". That means program management conclusively demonstrates that effort is not passing for results, tasks are not masquerading as requirements, and work is not being deferred that conflates "developer complete" with "user acceptance".
  4. Be an activist investor. As a board member, get your own data, form your own contra hypotheses, and engage in direct, constructive interrogation at board meetings. As a board member, you can talk to users, shadow teams, analyze delivery data, look at code and run analyses over that code. Nothing else will provide more effective leadership in these times from a governance role than investor activism that respectfully challenges those on the line creating a strategic software asset.
  5. Have at least one independent director on the governing board. Break up traditional governance structures by having independent directors with no connection to solution sponsorship, vendor representatives, or delivery managers. With no political, financial or emotional investment in any one or any thing, independent directors are better positioned to provide critical insight of the state and trajectory of the investment, as well as clinical recommendations for potential change.

Governance of strategic software investments does well to apply the standard of US <-> Soviet arms reductions treaties in the 1980s of "trust, but verify." Creating a no-trust governance environment is counterproductive. Low-trust environments are extremely dysfunctional and chaotic, and at best offer an anti-pattern for governance. That clubby team of vendor reps and ambitious managers doesn't perform well when at each other's throats like the crew of the ISS Enterprise in Star Trek: TOS. But a board driven by an activist chair and flanked by an independent director with a penchant for healthy skepticism creates an environment where trust is earned and re-earned, rather than tacitly given or outright kicked to the curb. That sets the tone for the board, delivery leaders and delivery partners, a tone especially valuable during a time when control is at a premium and trust is in rather short supply.

Sunday, May 31, 2020

Fundamentals

Last month, I wrote that the COVID-19 crisis has created prime opportunities for investing: depressed prices create opportunity to acquire assets that are likely to appreciate rapidly once the crisis passes. I also wrote that it is important to invest thoughtfully: fundamentals are changing, and without an appreciation for how those changes affect the economics of industries and value of assets, it is equally a prime opportunity to vaporize cash.

It is becoming increasingly likely that the COVID-19 crisis will result in lasting change in the ways companies operate. It will also encourage formation of new companies unencumbered by legacy assets and operating models. That will change the terms of what it takes to compete. Here are a few of the ways that might happen.

Corporate cost structures will change. According to the Wall Street Journal, employees and employers are finding it preferable to work from home and want to continue to be able to do so on a partial if not a primary basis. More employees working from home obviates the need for a lot of commercial office square footage. The Wall Street Journal also reported that some employers are looking at limiting the number of employees in the office on any given day as a permanent policy. Employees rotating through the office don't need (expensive) permanently assigned cubes and offices; (inexpensive) open space plans will do. Fewer in-person visits from recruits, vendors and customers means there will be little need for vanity offices in expensive cities. Not requiring consultant and contract labor to work on-site will reduce corporate travel costs. Of course, companies can't get free office space from their employees and expect the same level of productivity from them when they are working in a distributed manner. To support productivity of distributed workers, companies may offer a home-office improvement benefit to encourage increased comfort and productivity. Companies will also invest in increased task automation and activity surveillance to increase labor productivity and reduce labor intensity. As people become more proficient at working in a distributed manner, companies can employ people in any geographic market, giving them access to low-cost labor markets. They can also encourage existing employees to relocate to an area with a lower cost of living. A company that can source 25% of its work force from a location with a lower cost of living than where their employees are located today - for sake of example, suppose 20% lower - could shave 5% off its total labor costs. A shift to more people working from home represents a significant cost take-out opportunity for labor-intensive businesses.

Consumer transactions will change. Companies big and small have had to scramble to figure out how to create demand, take orders and fulfill orders just to stay in business. They've had to scramble because small merchants have largely relied on legacy consumer buying habits. A small merchant wanting to do more business digitally didn't have the balance sheet to finance development of digital capabilities, let alone drive consumer behavior change to use those capabilities. And, while there has been plenty of tech targeted at the small business, small merchants couldn't justify the fees as they could only realistically expect light trade activity through digital products. But with each and every small merchant facing the same adapt-or-die challenge, there is now a massive market of willing merchants and their customers. As a result, the race to improve digital capabilities for small merchants is now on, so there is reason to expect that considerably more innovation will be accessible to small merchants on a metered rather than a R&D basis. Still, the friction inherent in most transactions that has long been accepted as the norm for how business got done will increasingly become an exploitable weakness as consumers have become comfortable with new ways to transact. Today, you can't avoid going to the local hardware store to find the right replacement bolt, but when the big box DIY center allows you to snap a picture of the bolt from the comfort of your workshop, calculate the dimensions automatically, and have it delivered it to your doorstep in no more time than it would take to make a trip to the hardware store, that will reduce friction. That, in turn, means that the bad news for large merchants is that the tech arms race for frictionless commerce is only going to intensify. As Elaine Moore put it in the FT, having packages delivered to your doorstep is a hard habit to break.

Tax regimes will change. If employers perpetuate work-from-home practices long after the crisis passes, large cities such as New York will lose a great deal of their daytime population commuting in from suburbs. The Wall Street Journal reported a few weeks back that New York is losing mortgage- and rent-paying residents as people move out of the 5 boroughs to locations both near (New Jersey, the Catskills) and far (the North Carolina, Florida) from New York. Plus, reduced business travel means fewer people traveling to work in places like New York. A reduction in temporary and permanent population reduces taxable trade and taxable income. New York state and New York city tax receipts will drop as a result of depopulation and a reduction in trade and travel. That, in turn, will create pressure for increased taxes or entirely new forms of taxes on the people and companies that remain. Accountants and lawyers will be busy figuring out new ways to engage in legal tax avoidance, while companies will consider whether to relocate to where their former customers are, and to where the taxes aren't. It's also worth mentioning that federal tax policy might change, for example to allow more people to write-off dedicated home office space, giving people incentive to spend more on home improvement. It isn't difficult to imagine the DIY retailers lobbying congress to create legislation that allows employees to set aside up to x-thousand-dollars of annual income as tax exempt for use on home improvement. In the aggregate, there will be a free-for-all at the state level, as states grope for tax receipts in new and imaginative ways; at a federal level, never will have so many industry lobbyists ever have lobbied so hard.

Regulatory regimes will change. On the one hand, many regulations have been lightened to make it easier for companies to conduct business during the crisis. On the other hand, although big tech went from villain to hero in a short period of time because of the crisis, increased dependency on technology will bring renewed scrutiny to big tech. With more business being conducted digitally comes more opportunity for big tech to engage in surveillance activity, which will bring back calls for enforceable protection of digital privacy. This time around, it won't be for the benefit of individuals as much as it will be for large non-tech companies that find themselves increasingly dependent on big tech. Governments starved for tax receipts will also lean on big tech to collect, analyze and share data with government agencies looking for black market trade and illegal activities. Governments may also delay or restrict the deployment of technologies such as autonomous vehicles as a means of protecting service jobs - and the votes of people in service jobs. Because people don't have uniform access to technology, some segments of the population will face marginalization in an increasingly digital economy; that will motivate state legislatures to pass laws that compel technology providers to make technology more accessible.

Corporate IT costs will rise. People working remotely are for the most part working unsupervised (well, except for those on endless streams of conference calls). Some managers will believe they are not getting a full day's effort of their direct reports, trust relationships will be difficult to build with new hires who managers have interacted with primarily through video conference, and there will be incidents of remote-work abuse that erode manager-employee trust. New forms of employer surveillance tech will emerge, and if managers shift roles from salaried to hourly or piecework, that surveillance tech will need to be integrated to things like payroll. Information security costs will also rise: more employees are working from home creates more endpoints and more vulnerability to cybercrime. More people working from home will encourage (or require) employers to spend more on outfitting employees with better personal technology, and extend the scope of what technology is included in BYOD policies. Finally, an increase in digital trade will increase the need for more and faster technology to conduct that trade, amplifying the risk of frail legacy tech and accelerating the shift from solutions that are self-hosted to cloud.

Industries will change. A long-lasting reduction in demand for global travel makes it impossible for large airlines to service debt or top-up underfunded employee pension funds. A sustained reduction in demand for travel would be the knock-out punch for Boeing's commercial airplane business, already struggling as a result of a crisis of their own making. Airlines and large industrial firms are national champions and governments have a history of rescuing their champions. By way of example, nations have low tolerance to bank failures because the panic that results from them has knock-on effects in the financial and real economies alike (as exemplified by Lehman in September, 2008). From a certain point of view, a lot of banks were nationalized by governments in the wake of the 2008 financial crisis. In some cases, such as Lloyds and RBS in the UK, it was outright government ownership. In other cases, it was funding injected into banks through credit extensions or bond buying programs that removed assets from bank balance sheets to a central bank's balance sheet. In each case, it gave regulators license to give direct orders to the banks. Companies in industries that have little prospect of returning to pre-crisis norms may survive, but they will be unable to negotiate the terms of their survival. Detroit automakers - two of which were bailed out in 2009 - would have been content to retrench and resume selling light duty trucks at volume once demand recovered with the broader economy, but their lender of last resort set new policies for them to invest in electric vehicles. Airlines and commercial airplane manufacturers will similarly be given new marching orders.

Little or none of this may come to pass, of course. Testing, treatments and analytics may result in far less draconian methods of containment. Federal, state and municipal governments would all but mandate a resumption of pre-crisis business-as-usual, as that is the shortest and surest path to restoring economic health. But the longer the crisis lasts, the more employees develop new muscle memories for and discovering new productivity from working in a distributed fashion. The more comfortable employers get with that, the more likely these changes - and many more - will happen.

The effects won't be isolated. The interconnected nature of businesses and governments means an earthquake in one industry creates major tremors in quite a few more. Large-volume buyers of IT consulting services may no longer have to pay the 10% to 20% travel tax on that labor. That takes money out of the airline, hotel, rental car, and restaurant industries, which will translate into a drop in demand for direct and indirect suppliers to those businesses.

A company that is quick to adjust labor practices and PPE will be better prepared to navigate the labyrinth of new tax and bear the cost of new tech, and make it more resilient to shock waves of demand volatility and industry recalibration.

Thursday, April 30, 2020

Conserve or Invest?

Both the financial and real economies have suffered quite a few shocks in the last 20 years: the dot-com bubble bursting (2000); September 11 (2001); the Great Recession (2008); and today in 2020 the COVID-19 crisis is wreaking economic havoc. The crises have come with such frequency that executives leading companies impaired by the crisis already know the playbook: suspend the dividend, cancel any non-critical cash investments, negotiate with banks and bondholders to avoid defaults, pressure holders of hybrid securities to convert debt to equity, and progressively retrench business operations to reduced stages of life support. Uncertainty renders standard long-term planning inert, and by extension renders existing long-term plans superfluous since they were based on stable-state economic conditions of the normal credit / economic cycle. No company forecast the economy falling off a cliff in Q1 2020, so all bets are off.

But all bets are not off.

The thing about any crisis is that there's an expectation that there will eventually be a recovery, no matter long it takes to reach bottom and regardless the shape the recovery takes: V-shaped rebound as happened in in 1953, W-shaped as in 1981-82, U-shaped as in 1973-75 and again in 2000-03, or L-shaped as in 2008-2010. It might take some time and it might be a bumpy ride, but recovery will eventually come: free people in free markets are crowdsourcing at its very best.

Of course, in the midst of a crisis, there are no models that forecast economic performance to any useful degree of certainty. Making matters worse, conflicting and often erroneous real-time data leads to false optimism or false pessimism. The day-to-day nature of crisis management inevitably comes down to a focus on the two variables that affect the pattern of macroeconomic recovery: how bad, and how long? The more severe the contraction and the longer it lasts, the more people are out of work and the longer they are out of work. The longer that people are out of work, the greater the erosion to household savings and the greater the erosion of labor skills and subsequently the salary that labor can command once the job market recovers. This creates structural repression of demand. The longer it takes for demand to recover, the softer the labor market; soft labor demand twined with skill erosion means it takes longer for real wages - and therefore inflation, and with it standard of living - to recover. Tactical planning is informed by this negative feedback loop while a crisis is unfolding. To wit: the longer people are out of work, the fewer F150s are going to be driven off dealer lots once people feel recovery is at hand, the longer it will take for suppliers to Ford for the F150 to see a bounce in their business.

Regardless how bad it gets, there is a candle of hope perpetually burning in the expectation is that free human societies are resilient and will respond and innovate in the face of challenge and will ultimately be more productive and more effective on the other side. Recessions come and recessions go and yet despite the privations they bring, humanity has never had it so good. Thank you, economies that are not centrally planned.

Unfortunately, you can't take hope to the bank. In a crisis, everybody from heads of companies to heads of households conserve cash. Yet leaders have opportunities to be opportunistic buyers at prices they won't be able to get later. This is the challenge facing leaders during a crisis: balancing cash burn against an optimal state of the business to ride the recovery wave, whatever form recovery might take. For example, a company may have idle staff today because customers have suspended contracts, but paying for idle staff is a call option on rapid demand recovery and an insurance policy against loss of knowledge and capability. As CEO, you are making sure to signal your stakeholders that you are protecting investors and operations alike. But protecting operations is by definition an investment: if you're paying for idle labor, you're making a bet that preserving capacity will pay off sooner rather than later. And you're using that argument to fend off investors who are saber rattling for the cash on your balance sheet today, by arguing that paying them jeopardizes the sustainability of those cash flows tomorrow.

Another thing about crises is that recovery isn't uniform. The tech economy suffered greatly in the wake of the dot-com bubble bursting in 2000. In the years leading up to 2000, there was aggressive spend on technology: insulation against fears of the Y2K bug (legacy software and hardware with time functions that wouldn't properly roll over to 01/01/2000) as well as development of new business and consumer technology to exploit what was then nascent internet technology. Yet too many of those newfangled dot-com businesses had no real business plans, just naive enthusiastic capital propping them up. When the credit cycle turned in Q1 2000, non-cash-generative-tech-companies were exposed, plunging the tech economy into secular recession. Meanwhile, the emergence of internet technology had availed a skilled global workforce to deep-pocketed corporate IT buyers in Europe and the United States. So Y2K spend ends, dot-com spend ends, a less expensive workforce enters the labor market in massive numbers, all at about the same time. IT companies domiciled outside of the US boomed, the broader US economy hiccuped, and it was a bad time to be a US based software developer looking for work.

It was much different in 2008. The economy fell off a cliff with the Lehman filing in September 2008. Everything cratered, including tech, as banks - which had employed large numbers of tech people - laid them off. Yet while initially pro-cyclical, the tech economy was counter-cyclical by Q2 2009: that is, while the financial and real economies floundered, the tech economy was in full recovery before the first half of 2009 was over. Industrial firms that had laid off aggressively in the wake of the 2008 financial crisis needed to lock-in productivity gains for their reduced staff. Just a year earlier, Apple had introduced the iPhone 3G, which revolutionized smartphone technology and ushered in a new age of computing. Social media was just coming into its own. Tech became a hotbed of investment because tech was a source of opportunity. Demand for tech solutions and particularly demand for tech labor grew very quickly. Tech labor costs rose at a rate far above inflation. Non-tech companies had no real economy inflation to derive pricing power from, yet were forced to import tech economy inflation onto their income statements if they were to engage in meaningful tech investments.

In the current crisis, technology is playing an outsized role in enabling companies to operate under massively distributed conditions. While tech firms are not necessarily profiting wildly - usage of advertising-subsidized services is up but their advertising revenues are down, and there are more users of video conference software than there are paying licensees - usage of technology services, particularly collaboration infrastructure, has skyrocketed. Yes, we've seen that movie many times before in tech, and usage has a nasty habit of not converting into sustainable revenue. But as I've written before, tech doesn't lead disruption, socio-economic change does, and there's good reason to believe that there is lasting socio-economic change being established now ranging from consumer habits (e.g., retail square footage doesn't look like a good investment) to organizational dynamics (office square footage doesn't look like a good investment). If that change is durable, and tech is the enabling factor, then demand for tech - and by extension tech labor - will increase dramatically.

This is the leadership challenge of the current climate: cash flow from operations is down and investors are increasingly nervous, but the period during the crisis presents a prime opportunity to buy, especially if the economics of a tech investment are likely to invert post-crisis as labor prices rise.

To conserve or invest? It's a multivariate problem, and not an easy one. Here are some criteria to consider.

  1. Opportunity fundamentals I: robustness. To what degree is an investment deemed highly beneficial or essential in many-most-all forward looking economic models? A modernization or replatforming of core business operations is worth pursuing if it eliminates barriers to scale and labor intensity of operations such that the business scales down economically just as fluidly as it scales up. Such an investment makes the business more robust to volatile conditions and permanently changed conditions alike, and is worth pursuing.
  2. Opportunity fundamentals II: competitive threat. How easy is it for deep-pocketed competitors to use this time to enter into your space, how low are the switching costs for your customers, and what makes your current business vulnerable to the threat of a new entrant? An investment designed to make the business more resilient to future competition deemed highly probable is an investment worth making.
  3. Opportunity fundamentals III: speculative. To what degree is an investment dependent on criteria that were speculative pre-crisis only to be in gimbal lock today? For example, repackaging existing capabilities to pursue adjacent markets with which you have little familiarity is speculative use of capital. Pre-crisis, cheap capital could be lured to back a modest investment in a hypothesis supported by little intimate knowledge and thin data, as the potential payday of tapping into an adjacent market was worth the capital outlay. During a crisis, a hypothesis outside of your core business is just wishful thinking because you have little connection to those markets and therefore little appreciation for how the very fundamentals of that industry are changing in real time. With market instability and without context, these are not ideal circumstances for the shallow-pocketed novice to become a master.
  4. Asymmetric economics: to what extent is the investment dependent on labor that will become more expensive post-crisis? Few skill sets command premium wage during times of acute recession, but once the worst is over, some quickly appreciate in value due to demand outstripping supply, as happened a dozen years ago. Is the investment opportunity dependent on full-stack engineers? This is a great time to lock them in. Is it dependent on commodity ABAP developers? There is nothing to indicate that post-crisis their market rate will rise above pre-crisis levels, so there is little threat of economic inversion.
  5. Refocus: pre-crisis, it was plausible in many industries to plot strategies that balanced the status quo against a digital future. To wit: purely digital competitors don't suffer the economic burden of physical points-of-presence, but omni-channel experiences can transform physical presences into an experience that digital-only competitors can't match. Clearly, those physical locations and the labor that staff them are of no economic value when customers aren't leaving their homes. This crisis has very likely accelerated the digital trend, permanently moving more commercial activity from physical channels to digital channels. That, in turn, means that wagers on strategies linked to historical forms of customer interaction were at best a distraction at the time they were made, and has rendered them utterly useless investments in the here and now. Today, bunkered-up business leaders who made dud bets should be using this time to plot alternative "new normals" of their industries, and what it will take to succeed. If consumer and business buying patterns will be forever altered, best to be quick to meet the market where it is going; those are investments worth pursuing. Anything else - i.e., waiting to resume a prior investment trajectory, expecting previous demand patterns will return to pre-crisis norms - is value destructive.
  6. Capital mix: the higher a company's debt (assuming it isn't convertible), the greater the extent to which its cash is pledged to debt service. Capital injection isn't an option as investors would immediately conclude that their new capital would be used solely to service old capital. Investment is wishful thinking when your business is highly-levered because debt isn't loss-absorbing capital, it's cash flow absorbing capital. Recapitalization that exchanges debt for equity is an alternative: in times of crisis it gives investors the ability to swap short positions that are increasingly valued at liquidation pricing for long positions that have calls on future - if distant future - cash flows.
  7. Balance sheet strength: how strong is your balance sheet to define the future of your industry? Debt capital will likely be cheap for some time following the crisis. If you expect to come out of the crisis with asset values intact and for operating cash flows to recover quickly, you can expect to be able to go to bond markets and raise a war chest to go on an acquisition or investment spree. The ability to do that gives you the scale necessary to project influence over the future shape of an industry through consolidation, combination of services, pricing power, and innovation. Use uncommitted cash for investments in innovation today (remember, you're suspending the dividend), and cheap post-crisis capital for acquisitions later.
  8. Income statement strength: The balance sheet might be heavily laden with debt service obligations, but the income statement, even though suffering, might still be something you can leverage. Monopolistic or oligopolistic incumbents may very well stand to benefit from being first port of call once crisis conditions relax. Rapidly improving income will enable an incumbent to invade or greenmail upstart competitors who are similarly suffering. Income statement strength allows the incumbent to engage the upstart on the terms of the incumbent.

Conventional wisdom deems that a plausible response to crisis is aggressively retrenching, hoarding cash, and waiting it out. Waiting for what? Economic parameters and commercial patterns on the other side won't return to what they were before, and they will likely start to look considerably different very quickly. A business can survive the crisis only to be completely unprepared for the change that has taken place. Conventional wisdom really does exist so that people aren't required to think.

Baron Rothschild is credited with having said "the time to buy is when there is blood in the streets." This is one of those times. But it isn't just the times, it's where you want your business to be after the times. Simply surviving the present leaves you no better prepared for the future. Now is the time to build a case - rather, a lot of little cases - that project your influence over what the future of your business is to be.

Tuesday, March 31, 2020

Autonomy Now

Distributed software development has been practiced for decades. Companies with global footprints were experimenting with this at least as far back as the 1970s. Skilled labor, global communication networks and collaborative tools made "offshore development" possible at scale from the mid-1990s onward. Improved skills, faster networks and more sophisticated collaboration tools have made distributed development practical for very complex software initiatives.

There can be significant differences in the way a team collaborates internally, and the way it collaborates with other teams across a program. Consider a distributed Agile program consisting of multiple teams based in different countries around the world. Under normal circumstances, individual teams of 8 to 12 people work day-in and day-out with colleagues in the same physical location. Intra-team events take advantage of the team's close proximity: the team room, collaborative practices like pair programming and desk checks, team ceremonies like stand-ups, and low-fidelity information radiators such as card walls are all high-bandwidth collaboration techniques. In-person communication is robust, spontaneous and fluid, so it makes sense to take full advantage of it. Conversely, inter-team events such as a Scrum-of-Scrums involve only key team members such as the project manager and lead developer, and are scheduled to take advantage (or at least minimize the inconvenience) of time zone overlap. In practice, any single team in a large program - even an Agile team - can function internally in a tightly coupled manner even though it is loosely coupled to other teams in the same program of work.

The COVID-19 pandemic has a lot of the global work force working in physical isolation from one another; this pushes distributed work models to their extreme. Yes, of course, it has long been possible for teams of individuals to work completely remotely from one another: e.g., tenured experts in the relevant technology who are also fluent in the business context and familiar with one another. But most teams don't consist of technology experts who know the domain and one another. In the commoditized IT industry, people are are staffed as "resources" who are qualified based on their experience with relevant technologies. Domain expertise is a bonus, and interpersonal skills (much less familiarity with team-mates) never enter the equation. A good line manager and competent tech lead know how to compensate for this through spontaneous, high-bandwidth interaction: if somebody's work is going adrift, pull them aside, ask the business analyst or product owner to join you, whiteboard and code together for a bit, and get it fixed. A good line manager and tech lead compensate for a lot of the messiness intrinsic to a team of commodity-sourced people. The physical isolation much of the world is experiencing makes this compensation more difficult.

There are lots of companies and individuals self-publishing practical advice for remote working. Many are worth reading. Although the recommendations look hygienic, good remote collaboration hygiene reduces individual frustration and maximizes the potential communication bandwidth. An "everyone is 100% remote" from one another model has scale limitations, and poor hygiene will quickly erode whatever scale there is to be had.

My colleague Martin Fowler posted a two-part series on how to deal with the new normal. The posts have a lot of practical advice. But the concluding paragraphs of his second post address something more important: it is imperative to change management models.

Being independent while working remotely is not working remotely in an independent manner. The more tightly coupled the team, the more handoffs among team members; the more handoffs, the more people will have to engage in intra-team communication; the lower the fidelity of that communication, the higher the propensity for mistakes. More mistakes means lower velocity, lower quality, and false positive status reports. In practice, the lower the fidelity of intra-team collaboration of a tightly coupled team, the lower the fidelity of inter-team collaboration regardless they are tightly or loosely coupled.

This is where a distributed program of truly Agile teams has a resiliency that Agile-in-name-only teams, command-and-control SAFe teams, and waterfall cannot intrinsically possess by their very nature. A requirement written as a Story that fulfills the INVEST principle is an autonomous unit of production. A development pair that can deliver a Story with minimal consultation with others in the team and minimal dependencies on anybody else in the team is an autonomous delivery team. A Quality Assurance Analyst working from clear acceptance criteria for a Story can provide feedback to the development pair responsible for the development of the Story. Stories that adhere to the INVEST principle can be prioritized by a product owner and executed in a Kanban-like manner by the next available development pair.

A tightly coupled team operating in a command-and-control style of management doesn't scale down to a more atomic level of the individual or pair. The program manager creates a schedule of work, down to the individual tasks that will fulfill that work and the specialist roles that will fulfill those tasks. Project managers coordinate task execution among individual specialists in their respective teams. One project manager is told by three people working on tasks for a requirement that their respective tasks are complete, yet the whole of their work is less than the sum of the parts. Now the manager must chase after them to crack their skulls together to get them to realize they are not done, and needs to loop in the tech lead to figure out where the alignment problems(s) are. This is difficult enough to do when people are in distributed teams in a handful of office buildings; it's that much more difficult when they are working in isolation of one another. Product quality, delivery velocity, and costs all suffer.

Command-and-control management creates the illusion of risk-managed delivery at large scale with low overheads. Forget about scaling up with efficiency; to be robust, a management paradigm needs to be able efficiently to scale down to deliver meaningful business results at the atomic level of the individual or pair. Micromanagement does not efficiently scale down because of the inherently high overheads. Self-directed autonomous teams do efficiently scale down because of the inherently low overheads.

In 2013, I spilled a few photons on the management revolution that never happened: for a variety of reasons in the 1980s, we believed we were on the cusp of a devolution of authority; instead, we got much denser concentration of authority. In 2018, I spilled a lot of photons on autonomous teams at enterprise scale being an undiscovered country worth the risk of exploring.

The COVID-19 pandemic is creating intense managerial challenges right now. It is important to note that there are likely to be long-term structural effects on businesses as well. Perhaps companies will encourage employees to work from home more regularly so the company can permanently reduce office square footage and therefore lease expense. Perhaps a new generation of secure mobile technologies will make it seem idiotic that large swaths of workers are office rather than home based. Perhaps companies will revise their operating models and position specs, requiring greater individual role autonomy to maintain high degrees of productivity in regular and irregular operating conditions. Perhaps metrics for contract labor - metrics that are not attendance based - will emerge to satisfy expectations of value delivery.

Perhaps, with the potential for long-term effects looming, it is time to go explore that undiscovered country of autonomy.

Saturday, February 29, 2020

To Transform, Trade Ego for Humility

Ten years ago, when the mobile handset wars were in full swing, I wrote a blog analyzing the differences among the leaders in the space. Each had come to prominence in the handset market differently: Nokia was a mobile telephony company, Blackberry a mobile email company, Apple a personal technology company, Google an internet search and advertising company.

With the benefit of hindsight, we know how it played out. Nokia hired a manager from Microsoft to wed the handset business to any alternative mobile operating system to iOS that wasn't made by Google. RIM initially doubled down on their core product, but eventually scotched their proprietary OS in favor of Android. Neither strategy paid off. Nokia exited the handset business in 2013. RIM exited the handset business in 2016. Both companies burned through billions of dollars of investor capital on losing strategies in the handset market.

There has been evidence published over the years to suggest that the self-identity of the losing firms worked against them: interactions via voice call and email had less overall share time on mobile devices, overtaken by emerging interactions such as social media. By providing a platform for independent software development, an entirely new category of software - the mobile app - was created. iOS and Android were well positioned to create and exploit the change in human interaction with technology. Nokia and Blackberry were not.

* * *

Earlier this week, Wolfgang Münchau posited that the European Union is at a cultural disadvantage to the United States and China in the field of Artificial Intelligence. Instead of finding ways to promote AI through government and private sector development and become a leader in AI technology, the EU seems intent on defending itself from AI through regulation. For that to be effective, as Mr. Münchau writes, technology would have to stop evolving. Since regulators tend not to be able to imagine a market differently than it is today, new AI developments will be able to skirt any regulation when they enter the market. It seems to be a Maginot Line of defense.

When it comes to technology, Mr. Münchau writes that the European mindset is still very much rooted in the analogue age, despite the fact that the digital age began well back in the previous century. This is somewhere on a spectrum of a lack of imagination to outright denial.

That begs the question: why does this happen? In the face of mounting evidence, why do people get their ostrich on and bury their heads in the sand? Why does a company double down instead of facing its new competitive landscape? Why does the leadership of a socio-economic community of nearly 450 million people simply check out?

Mr. Münchau points out three phenomenon behind cultural barriers to adaptability.

The dominant sentiment in modern-day Europe is anxiety. Its defining need is protection. And the defining feature of its collective mindset is complacency. In the European Commission’s white paper on artificial intelligence all three come together in an almost comical manner: the fear of a high-tech digital future; the need to protect oneself against it; and the complacency inherent in the belief that regulation is the solution.

What stands in the way of change? Fear. Resistance. Laziness.

* * *

Some executive at some company believes the company needs to change in response to some existential threat. That which got it here will not take it forward. Worse still, its own success is stacked against it. What we measure, how we go to market, what we make, how we make, all of that and more needs a gigantic re-think. Unleash the dogs of transformation.

In any business transformation, there is re-imagining and there is co-option. Wedding change to your current worldview - your go-to-market, your product offering, your ways of working - impairs your outcomes. At best, it will make your current state a little less bad. Being less bad might satiate your most loyal of customers, it might improve your production processes around the margins, but it won't yield a transformative outcome.

Transformation that overcomes fear, resistance, and laziness requires doing away with corporate ego. "As a company, we are already pretty good at [x]." Well, good for you! Being good in the way you are good might have made you best in class for the industry you think you're in. What if instead we took the position, "we're not very good at [x]?" General Electric's industrials businesses grew in the 1990s once they inverted their thinking on market share: instead of insisting on being the market share leader, GE redefined those markets so that no business unit had more than 10% market share. That meant looking for adjacent markets, supplemental services, things like that. It's hard to grow when you've boxed yourself in to a narrow definition of the markets you serve; it's easier to grow when you give yourself a bigger target market. That strategy worked for GE in the 1990s.

Re-imagining requires more than just different thinking. It requires humility and a willingness to learn. From everybody. The firm's capital mix (debt stifles change, equity does not), capital allocation processes (waterfall gatekeeping stifles adaptability), how it sees the products it makes (software and data are more lucrative than hardware), how it operates (deploy many times a day), must all change. That means giving up allegiance to a lot of things we accept as truth. This is not easy: creating a learning organization embraced by investors and labor alike is very difficult to do. But if you're truly transforming, this is the price of admission if you're going to overcome resistance and laziness.

What about fear? Those who truly understand the need to transform will face their deepest fear: can we compete?

In the span of just a couple of years, two deep pocketed firms with healthy growth trajectories introduced mobile handset products and services that eclipsed the functionality of incumbent offerings by 99%. The executive who understood the sea change taking place would not concoct a strategy to fight the battle on their terms. That executive would try to understand what the terms of competition are going to become, and ask if the firm had the balance sheet to scale up to compete on terms set by others.

Mr. Münchau points out that the same phenomenon may be repeating itself among Europe's automakers. They got a late start developing electronic vehicle technology. With governments mandating electrification of auto fleets, the threat is not only real, it's got a specific future date on it. Hence there has been increased consolidation (proposed and real) in the automotive industry in the past decade: an automaker needs scale to develop EV technologies to compete. Those automakers that have consolidated are accepting at least some of the reality that they face: automakers as national champions that create a lot of high-paying industrial jobs struck a balance among public policy, societal interests, and corporate interests for many decades. The change to EV technology is challenging the sustainability of that policy. If the enormity of fighting outdated public policy weren't enough, carmakers moving from internal combustion to electricity also face the transition from hardware to more of a software mindset. The ways of working are radically different.

The firm that truly needs to transform doesn't have the luxury of doubling down on what it knows. It must be willing to give up on long-held beliefs, change its course of action when the data tells it that it must, and face the future with a confidence borne of facts and not conjecture. It must trade ego for humility.

Friday, January 31, 2020

Lost Productivity or Found Hyperefficiency?

Labor productivity creates economic prosperity. Increasingly productive labor results in lower cost products (greater output from the same number of employees == lower labor input costs), higher salaries (productive workers are valuable workers), greater purchasing power (labor productivity allows households to keep monetary inflation in check), increasing sophistication (skill maturity to take on greater challenges), and higher returns on capital. The more productive a nation's workforce, the higher the average standard of living of its population.

In recent years, economists have drawn attention to low productivity growth in western economies as a key factor restraining economic growth and perpetuating low inflation and low interest rates. In particular, they cite the lack of breakthrough technologies - e.g, the emergence of the personal computer in the 1980s - to spur labor productivity and with it, more rapid economic growth. By traditional economic measures, things do not appear to be getting much better.

There is an alternative perspective that is far more optimistic: digital companies drive down costs through hyper-efficiency (speed, automation and machine scale) and price transparency. Algorithms are cheaper than humans and can be networked to perform complex collections of tasks at a speed, and subsequently a scale, that humans cannot achieve. Twined with the radical reduction of information asymmetry (particularly with regard to product price data), it stands to reason that there has been significant productivity growth in western economies: supply chains have never been so optimized, retail and wholesale transactions so price-fair and friction-free. This stands to reason: it is considerably less time- and energy-intensive to ask an Echo to order more Charmin toilet paper than it is to drive to a grocery store or pharmacy, walk in, price compare to justify those few extra pennies for softness, queue, pay, and drive home. The argument for this invisible efficiency is that economic models have simply failed to change in ways that reflect this phenomenon. The productivity is there, and will intensify with technologies such as AI and ML; the instrumentation simply doesn't exist to measure it.

In this definition, productivity through technology is a deflationary force that makes products more affordable. Even if real wages remain stagnant, the standard of living increases because people can afford more goods and services as they cost less today than they did yesterday. In theory, the increasing standard of living will occur regardless the cost of capital: because retail prices are going down, interest rates could move higher with no ill effects to the economy, juicing returns on capital. The bigger the tech economy, the better off everybody is.

There is truth to this. Consider healthcare: although medical costs are much higher today in nominal terms than they were in 1970, they are much lower in real terms when adjusted both for monetary inflation and medical-technological innovation. If medicine were still practiced today as it was 50 years ago, the cost of delivery would be lower in real terms, but the standard of care would be much, much lower than what it is today. Would you want to receive cardiac treatment at a 1970 standard, pulmonology treatment at a 1980 standard, or HIV treatment at a 1990 standard? Or would you rather be treated for all of these to a standard of care available in 2020? Technology is clearly a deflationary force that increases individual prosperity.

Still, there are three factors that should temper enthusiasm for an unmeasurable tech-led labor productivity bonanza.

The first has to do with the real price of and the real payers for tech-generated benefits. Ride sharing services have added driver/fleet capacity and accelerated speed-of-access for local transportation service. However, the individual consumer isn't fully picking up the tab; the ride is heavily subsidized by private capital. That makes the price affordable to the user. The question is, how sustainable is the price without the private-capital subsidy?

Economic subsidies are a common practice, typically sponsored by governments to protect or advance economic development. Sometimes a subsidy is direct, as is often the case with agricultural commodity price supports: if depressed crop prices drive farmers out of business, a nation loses its ability to feed itself, so in years of commodity gluts governments will offer direct assistance to make farmers whole. And, sometimes a subsidy is indirect. The United States was dependent on oil from foreign countries for much of the past 60 years. The price of petroleum products in the US did not reflect the cost of US military bases as well as having the Fifth Fleet patrol the Persian Gulf. The federal government prioritized energy security to guarantee supply and reduce the risk to energy prices of supply shocks. The immediate cost of that security and stabilization was borne by the US taxpayer; the policy was founded on the expectation that the federal government would be made whole over the long term through increasing tax receipts from economic growth that resulted from cheap energy.

There are subsidies that are sustainable and subsidies that are not sustainable. In theory the US projecting military power to secure Middle Eastern oil was a sustainable economic subsidy: containing energy prices while your nation gives birth to the likes of Microsoft and Apple and many other companies seems a good economic bargain (exclusive of carbon emissions, which did not historically factor into economic policy). By comparison, productivity in the Soviet Union grew in lock-step with direct government investment in industry (primarily steel production) through the 1950s and 60s, Trouble was, when the Soviet government pulled back investment, labor productivity growth flatlined. Labor productivity was entirely dependent on outside (e.g., government) financial injection. The lack of organic productivity growth translated into stagnation of economic prosperity of the masses. A standard of living that was competitive with the United States and Western Europe in the 1950s was hopelessly trailing by the 1980s. Turns out Maggie was right: eventually you really do run out of other people's money.

The investment case for the ride sharing companies is that there will eventually be one dominant player with monopolistic pricing power. A market for on-demand transportation is now established, so a single surviving ridesharing firm will reap the winner-take-all benefit of that market, giving it scale. Being the only game in town, the surviving firm will have pricing power. In theory, the surviving firm should have access to a larger labor pool spanning Subaru drivers to software developers, thus depressing wages, and thus the cost of service. Lower input costs twined with scale should mean a lower price increase is needed for the firm to become profitable.

But there are a lot of variables in play here. Ridesharing firms are carrying billions of dollars of losses they accreted over many years that they need to make up for their investors to be made whole; that will create pressure to raise prices. There are other industries competing for the labor of these firms (especially those software developers), so input costs will not necessarily decline. Because drivers work for multiple ridesharing services, their utilization is already high, meaning economies of scale that will temper price increases passed on to consumers.

If or when a monopolistic competitor triumphs, prices are going to rise and individual consumer's "productivity" will be impaired by the withdrawal of the price subsidy. Consolidation and scale will not perpetuate the subsidy, so the price of service is going to rise. The subsidy is only sustained if a new entrant with deep-pocketed backers emerges to challenge what will by then be a "legacy" incumbent; in essence, the cycle of subsidy regenerates itself. Don't rule it out: it isn't out of the question as long as capital is cheap. While it's reasonable to assume the industry will run out of greater fools, there has always been a high degree of correlation between "minutes" and "suckers born". The WSJ reported today that Softbank is pumping cash into multiple meal delivery services operating in the same markets and therefore competing directly with one another, each firm engaged in an arms of subsidies with one another to sign restaurants, delivery labor and customers. It is difficult to fathom the logic of this.

The second factor is the implicit assumption that the tech cycle has triumphed over the credit cycle. There is a popular theory that technological innovation has become more important than capital in setting prevailing economic conditions. The evidence of this is the shift in economic activity steered by emerging technologies in areas such as ecommerce and fintech. A technology-centric business benefits from lower costs for facilities, lower inventory carry costs, and lower network (transaction) costs, and therefore has an intractable competitive advantage over incumbents. As I've written previously, unfortunately the evidence doesn't entirely support this yet. Plus, deep-pocketed incumbents can raise capital to acquire, compromise or corrupt the business models of would-be disruptors, not to mention that would-be disruptors are finding themselves engaged in technological arms races not with incumbents, but other would-be disruptors. This distorts the playing field, making it much more about capital than tech.

It's curious that contemporary strategy among big tech firms is to burrow into the existing economy as un-metered, un-regulated, subscription-based utilities, as opposed to betting on ever-accelerating revenue from their intrinsic value-generative nature. Consider entertainment streaming services: by selling subscriptions, they are willfully exchanging the potential for sky-high equity-like returns from the value of the content they produce (which is how movie studios used to operate) for more modest debt-like returns from the utility that subscribers will pay for access to a library where they can find something they can tolerate just enough to pass the time (which is how cable companies operate). While streaming services are engaged in a long-running competition for content and tech, they have concluded they are not going to win by out-tech-ing or out-content-ing one another. Streaming entertainment is not a value proposition, it is a utility proposition. A utility business model is one that is explicitly (a) not leading with tech innovation and (b) seeking immunity from the credit cycle.

What this tells us is that the tech cycle is not the dominating economic force. As it stands today, more people suffer economically when the credit cycle turns than when the tech cycle turns (e.g., a dearth of innovative new technologies). A turn in the credit cycle contracts business buying which creates layoffs. A turn in the tech cycle makes means there will not be a still more convenient way to get a ride from The Loop to O'Hare or food delivered from a Hell's Kitchen restaurant to an apartment in Midtown. While it may happen some day, we are still not yet at a point where the tech cycle is triumphant.

The third factor goes to the question of labor capacity versus labor productivity. Labor productivity and labor-saving efficiency are really measures on the same axis: less time, effort and energy necessary to complete a task and ultimately achieve an outcome. A different but equally important dimension is labor capacity: the more people engaged in gainful employment, the greater the level of household income, the more individual households reap economic benefit.

Labor participation in the United States took a direct hit in September, 2008, and hasn't recovered. After hovering above 66% for over 18 years, it went into sharp decline, bottoming at 62.5% in 2015 and recovering only to 63.2% today. To put it in absolute terms, there are 20 million more jobs in the US today than there were in 1999 (peak labor participation), but the US population has grown by 48 million more citizens. Job growth hasn't kept pace with population growth. This suggests that the economic benefits of productivity gains (through organic labor productivity or technology) are concentrated in fewer hands, implying that the economic benefits of technology gains are asymmetrically distributed.

Yes, labor capacity is a measure, not a driver. From 1950 to 1967, the labor participation rate hovered in the 59% range. And even with a growing population, technological advances can create price deflation that raises the standard of living for everyone: many and perhaps most of those 48 million additional US citizens since 1999 have smartphones, which none of the 279 million Americans had in 1999. Still, there is asymmetric benefit to those technological advances: those not working are not enjoying the totality of economic benefits of increased productivity described in the opening paragraph. As much as proponents advocate that technology improves labor productivity, that same tech is also increasing in the Gini coefficient.

Does technology improve productivity? Undoubtedly. But before hailing any technology as an economic windfall on par with traditional measures of labor productivity, best to scrutinize how it organically it achieves it, how resilient it is, and how widely its benefits are spread around the work force. Technology may eventually change traditional economics, but there is one thing even the best technology cannot overcome: there is no such thing as a free lunch.