The Soft Underbelly of Technology Services

I spend a lot of time thinking about delivery models for technology, especially in an age of shrinking budgets and growing complexity.  So I was struck to read that Avanade, a joint custom software venture between Accenture and Microsoft, had been sued by a customer for major cost overruns.  The key part:

The lawsuit said a software project estimated to cost $17 million and take 11 months instead mushroomed to $37 million over three years, and ScanSource said it still doesn’t have a Dynamics software up and running. Accenture has estimated it will cost $29 million more to complete the ERP project, according to ScanSource’s lawsuit.

What can be learned from this? There are quite a few things.  The cynics among us might point out that an overrun of $20 million and 2+ years is considered a bargain in some areas of government.  That is of course an outrage, but the important takeaway goes beyond the numbers, to the fundamental nature of the delivery model.  Let’s assume for this conversation that actors all good faith and very competent here.  I think that despite that, the model leads to these sorts of outcomes.

Not surprisingly, Avanade turns out to be in the business of renting labor.  Services is the exact wrong model – a catastrophically incorrect model, the more you think about it. These sorts of incidents are really a lagging indicator of the weakness in the model, but it’s taking a whole lot of innocent (and some not-so-innocent) bystanders with it.  More on them in a few.

There are many shortcomings to services model, but most fundamentally it’s the wrong incentive structure.  When you’re renting labor and other nebulous inputs, it’s almost a truism to point out that the longer it takes, the more the company prospers, and the bigger the project, the more room for abuse.  A contractor doing a bathroom remodel might employ a similar cost structure, but could never get away with overruns on a tenth the scale of those alleged in the Avanade lawsuit.  Of course, even if you have reliable cost safeguards in place, custom software development is inefficient, as I’ve often railed about in these pages.  It takes an army of consultants to deliver, and another army of consultants to maintain.  

It’s not all the services company’s fault, though – not even primarily.  In a sense everyone is complicit, from the services company, to the customer who doesn’t demand something better or structure payment to be a premium but based on success, to the tech giants who aren’t working to productize services.  Of course, if product companies dared to do so, the services companies of the world would throw a fit, and professional courtesy runs deeper than you might think in a theoretically competitive marketplace.  

When the world changes, you don’t always get a say in the matter, and evolution has a funny way of sneaking up on those who get too comfortable.  The first indications may just be bubbling to the surface, but two things are clear: services companies are under tremendous pressure, and product companies need to productize services. 

The first point makes sense from a valuation standpoint.  Mature tech companies such as Oracle and Microsoft have market caps of ~5-6x annual revenue, while the multiple is often less than 2x for services firms, even the upper tier.  Yet it’s still not obvious to all that services companies are living in the past (partly because many services companies are so good at convincing people they’re really technology companies).  Mostly, though, it’s because services companies still generate a lot of money.  It’s a dying model that’s still making people rich, so it’s easy to ignore the warning signs even if you see them.  And for an exponential trend, by the time you are 1% there, it is almost done.  You could almost analogize it to the SUV craze: consumers couldn’t get enough gas-guzzling SUVs, and American auto makers happily served them up for several years.  Suddenly (but not all that surprisingly), $3-4/gallon gasoline was a fact of life and those same automakers were all teetering on bankruptcy for giving the customers exactly what they wanted.

In terms of multiplying complexity and data problems, we’re entering an era of $10/gallon gas.  Even if you’re in the product business, if you’re not increasing your productivity per person, you are dying – in some cases more quickly and dramatically than the services dinosaurs.  And for this reason, product companies can’t just deliver products any more – they need to productize services on a continuous basis.  In short, they need to deliver outcomes.  Mere capabilities only work against well understood problems.  They won’t be sufficient for the types of challenges that grow appreciably bigger in the time it takes to read this blog post.  

If that sounds smug, it needs to be acknowledged that building a business based on outcome delivery, as opposed to a static product, is still extraordinarily hard.  Not only are the prevailing incentive and cost structures far behind, but technically speaking it’s a very rugged frontier.  This is perhaps best illustrated by software, where performance at scale, processing, security, stability, and interoperability are often much bigger challenges than achieving the desired functionality.  On the other hand, though, successful technology has always productized services of some kind, dating back as far as the cotton gin or even the wheel.  The entropy of the present and future data landscape adds an enormous degree of difficulty, but along with Moore’s Law, the single biggest lever of the knowledge economy is the ability to repackage experience and lessons learned into a better, more responsive product.  It may take years or even decades, and it’s entirely possible that the first mover will end up being a sacrificial lamb.  Sooner or later, though, the company that gets productization right will eat the legacy companies’ lunch.