Nearly 30 years ago, businesses across the world began a surge of investment in information technologies. Spurred by desktop computers that were fast enough to run graphical user interfaces, by the adoption of the Internet starting with email, and by the combination of management consultants and enterprise software vendors, companies began “reengineering the corporation,” as one best-selling book termed it. Chief Information Officers were named and, with great rapidity, often replaced. SAP, Siebel, Oracle, Sun Microsystems, and Microsoft all minted millionaires out of programmers and architects, while the big systems integrators — IBM, Accenture, and many others — hired, trained, and churned through thousands of young hires to staff the many and massive projects. As for results, opinions varied in both academic and managerial circles, but every CEO, no matter what industry, had to confront the decision as to how (not whether) to invest in IT.
There are reasons to wonder whether the time has come for a similar wave. Machine learning has dropped in price and proven its capabilities to help address new kinds of problems. Cloud services have changed the capital spending landscape sufficiently that IBM is spinning out everything else and focusing 100% on virtualized computing. Internets of things, industrial and consumer alike, create stunning possibilities for improvements in efficiency, safety, and innovation. New languages and architectures including Tensorflow, containers, adaptive processing platforms like FPGAs, and no-code development tools extend both the making and using of enterprise computing to new scenarios. And no longer are programmers limited to Microsoft, Oracle, and the usual developer toolsets: Zoom just announced it wants to be a platform, joining the likes of Slack, Dropbox, and of course Salesforce.
There’s a growing list, most recently driven by Covid-19, of consequential business and social problems that require attention. The good news is that the aforementioned technical developments make new solutions (and types of solutions) possible. Finally, businesses need the kinds of transformations that IT makes possible. Amazon’s scale, Airbnb’s flexibility, Google’s reinvention of the advertising industry: none of these competitive forces could run on 1990s computing. Whether it was the lengthening of global supply chains, the offshoring of millions of western jobs, or the complex financial instruments that made modern banking possible, modern business relies on more and more complex software applications, ideally accessible anywhere any time on any device.
Why will this time be different? I’ve spotted many reasons, and readers will no doubt have even more. Let’s look at a few.
1) The global pandemic will make capital spending extremely challenging
Yes interest rates look like they will remain low, facilitating borrowing. But the uncertainty of the pandemic’s initial duration along with the virus’s long-term effects, susceptibility to vaccines and/or therapies, and potential mutation will not clarify for years. Hard-hit industries continue to multiply: travel and tourism, hospitality, oil, retail, and the public sector only begin a list. Corporate spending on anything investigative is likely to remain constrained for 3 years, probably more.
2) The IT vendor landscape is changing
In the old days, “nobody ever got fired for buying IBM.” Later, duopolies or oligopolies emerged in sector after sector: databases (IBM, Oracle, and Sybase or another flavor of the month), enterprise operating systems (Unix variants, Windows NT), networking (Cisco and Juniper), and so on. Now, several factors represent a changed landscape from 15 years ago.
A) The installed base is a complex mess of new and old; on-premise and cloud; startups, warhorses, and unsupported failed companies; mobile and desktop; top-down and bottom-up; free and licensed; and backbones from accumulated merged entities. “Greenfield” is a ridiculous notion in this day and age.
B) Virtualization has destroyed the old ISO “layer cake” model of who did what. Is a storage area network storage or networking? Given that a social graph is a database, can our DBAs run one? Is Google Maps data or application? VMWare, a software company 80% owned by Dell, a hardware company, sells virtualization that runs on Amazon's AWS. Who's the lead dog on that sled? Figuring out which vendor can, should, and will do what, especially in the aforementioned complex legacy environments, is nontrivial.
C) The IS shop can no longer play gatekeeper. Beginning with Salesforce, business units and even departments began bypassing central IT and expensing SAAS seats that solved real problems, ramped up in days not months, and avoided the types of IT staffers who were either too intrusive (“you need to do it this way”) or unresponsive (“fill out a trouble ticket and we’ll sort them by priority”). In some companies, central IT tried to block Facebook at the firewall, smartphones notwithstanding.
D) While there are still big vendors selling IT, the buying environment is more complex. “One-stop shops” are harder to find. SAP stock fell 20% in one day a week ago. IBM is reorganizing, again. Amazon does AWS extremely well, but it’s not a holistic solution, especially absent pretty capable developers to deploy it on the client side of the relationship. The trend toward process outsourcing means that Accenture might run a big chunk of a company’s supply chain, but the outsourcer’s handoff points to both IS and internal SCM are far from standard or fixed. And what the contract says might not be how things actually work on the ground. Thus the days of Oracle, Deloitte, and Compaq teaming up on a big bid look very different: recall that a recent government cloud contract came down to AWS and Microsoft after Oracle and IBM were eliminated.
3) Today’s business problems are different than 1995’s
Whether it’s computational biology at a pharma company, chatbots in customer service, detecting synthetic media (deepfakes) in video on social media, or administering fair tests via online instruction, the enterprise software of the past decades won’t have, or be able to accommodate, the machine-learning and other computational resources to address many of these evolving business needs. The jokes about ERP and poured concrete resonated for a reason, and in a world where international trade agreements can change weekly, terrorism and sabotage take new forms, and markets can evaporate overnight (hello air travel), agility has become a watchword that big software packages typically don’t speak.
4) Today’s organization is different from 1995’s
Remote workers and the new childcare realities that they bring, contractors with evolving legal status, offshore factories migrating closer to (maybe not “back”) home, pressure from multiple sides to address racial and gender equity issues, people at retirement age staying on given insufficient 401(k) savings, and the need to recruit millennials with different skills, norms, and values from the core staff — it’s hard to see much business as usual, and the upheaval will increase, not decrease, in the foreseeable future. The call to be “data-driven” echoes from the C-suite outward, but people with the skills to do and to manage such processes are not yet available in sufficient numbers. (If anything, scientific and quantitative literacy in the U.S. are declining.) Deciding to do the right things is a key part of management, but doing those things right is tough if the requisite skills are just not available.
Finally, this time will be different in part because some things stay the same. People still resist change, personally and especially collectively. Most organizations, ERP investments notwithstanding, still run on Excel + email. Work/life don’t balance. Risk-taking has been suppressed by “risk management” departments to the point where the status quo becomes organizational law.
If it’s going to be different, what should we look for this time around?
Privacy, algorithmic transparency, and naïveté all need to be addressed by substantive debate and laws with teeth: people have proven incredibly easy to game and the massive behavioral experiments being run by Google, Facebook, and Amazon have concrete consequences. In enterprise IT, meanwhile, when cash is king, customers can extract real change from vendors. Finally, maybe some organizations won’t waste a good crisis and instead begin the hard work of reinventing the cost structure rather than nibbling at it, the value proposition by truly engaging with customers, and the organization by taking a hard, fresh look at what’s possible and sustainable. (The Nordic countries are one place to start.)
Jeanne Ross is a longtime fixture at MIT’s Center for Information Systems research, having been director and now Principal Research Scientist in nearly 30 years there. In her new book Designed for Digital, she and two co-authors look at the IS organization that is emerging in the post-ERP/CRM era: these backbones are necessary but not sufficient, and IoT, machine learning, analytics, blockchain and many other emerging technologies need to be assessed and where applicable utilized. Her exemplars of “big companies that get it,” drawn from the CISR’s global roster, might be surprising but I can attest, after seeing hundreds of mid-career masters students, that Schneider Electric and Philips are in fact making positive moves.
There is a lot to learn from in the book, but three core lessons from the leading companies apply in the context of this newsletter.
1. They experiment repeatedly.
2. They co-create with customers.
3. They assemble cross-functional development teams.
In Ross’s words, “These three challenges attack your habits because they tend to be different from what you have done.” In other words, it’s the behaviors that matter, not the change management consultants, or the CIO who has “a seat at the table” (most still don’t), or the project’s projected ROI.
In learning from startups, Ross notes that big companies don’t really get the notion of the pivot, of starting down a road then changing course after new information becomes available. Yes the established company has channels to market, capital, and brand equity the startup lacks, but, in the end, the startup poses a threat to the incumbent for this single reason: small, open-minded organizations are better at changing their mind and shifting direction in light of experimental evidence.
Thus the short answer to the opening question — why will things be different this time? — is that size matters, and small is beautiful because agility often matters more than mass. For many reasons, look not for 5-year $50 million transformations, but rather quick-hit, small-scale pilots with the freedom to evolve and ideally pivot.
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