One of my very first jobs was for a concrete pipe company that was in the middle of a lawsuit. It needed a way to code their documents so its lawyers could find required information and so it could respond to discovery demands.
My job was to write a small piece of software to help them do this and then actually do the coding process.
I hammered out my snazzy little program and tested it on the handful of documents they had given me to use. And it worked perfectly. Then they walked me into the room where they kept the records for the lawsuit. There were thousands of boxes!
It became instantly clear that the new, automated process I had built worked great when I was talking about a few documents, but it was not going to be nearly as easy once I was dealing with hundreds of thousands of them.
As enterprise leaders begin to take their initial efforts around things like DevOps, Agile, data science, and related new approaches and attempt to scale them to meet broader enterprise needs, they are getting a bit of that same sinking feeling that I felt as I walked into that room.
Despite all the talk and hype around these new approaches, the challenges that enterprises encounter as they attempt to scale these efforts is why most organizations still use waterfall approaches and legacy management technologies and approaches across much of their legacy technology stack.
But as most enterprise leaders realize, we are reaching a breaking point in which they must find a way to scale these efforts if they are to truly transform their organizations. But how?
Victims of Their Own Success
Rightfully, most enterprises took their first steps with these new approaches by starting with a clean slate.
These so-called greenfield projects did not have to deal with any of the legacy challenges of the legacy stack. In most cases, organizations formed separate teams that adopted these approaches, and their associated technologies, and gave them targeted, often disruptive, project mandates.
Because of their often disruptive nature, these projects also tended to be non-core, meaning they were all upside and little downside. If they failed, they were just a failed experiment that cost some time and money. But if they paid out, the payoff would be huge.
And pay out they did.
Over time, of course, these projects became more important and business critical for organizations trying to stave off disruptive threats or find openings in emerging markets. Still, however, these new efforts remained mostly — and gleefully — free of the legacy stack’s less desirable situation: all downside risk with little upside.
As the wins piled up, it was only natural that enterprise leaders would start asking why the organization wasn’t applying these approaches, principles, and technologies everywhere.
But it was about more than just a natural progression. As the customer experience — particularly in the context of the full customer journey — has become a more significant driver of business value, these left-behind legacy systems have once again become a vital part of the process — and a constraint that organization must now remove.
All attention has, therefore, turned to taking these winning approaches, tools, and technologies and deploying them across the entirety of the enterprise technology stack.
But that’s proving to be anything but simple.
Looking at Scalability the Wrong Way
Whether it’s DevOps or data science, there are two significant challenges organizations face when they seek to move beyond targeted use cases and look to deploy any modern approach more broadly across the enterprise.
The first is that they look at scaling as predominately a technology problem — that it’s about deploying the right tools, technologies, and new technology approaches across the organization.
The second is that they see scaling as a question of multiplication — they figure that they just need to take what is working and multiply across the rest of the organization.
While there is an element of truth to both of these beliefs, they fail to address the most significant challenges that organizations face as they seek to scale these efforts: complexity and culture.
The enterprise legacy stack is both complex and rigid. Both attributes run headlong into the ethos of speed and agility that is central to virtually every modern approach. It is because of this complexity and rigidity, in fact, that there is such a desperate need for organizations to apply these approaches in the first place.
But because of these factors, it is foolhardy to think that you can simply apply these modern approaches without adapting them to deal with this complexity and rigidity.
And it’s not just the technical complexity and rigidity, however, that slows down scaling efforts.
Perhaps even more significant are the complexity and rigidity of the culture and structure of most enterprise organizations.
Whereas organizations built their new DevOps, agile or data science teams from the ground-up as purpose-driven and cross-functional teams, the rest of the organization is often organized around specialization and segregation — leading to silos and plenty of challenges around miscommunication, coordination, and bureaucracy.
Here too, new approaches are supposed to help overcome these issues, but they are no panacea and organizations cannot merely heave them over the wall and expect them to transform long-standing cultural norms and organizational inertia somehow magically.
The Tool Gap
While the technical and cultural complexity and rigidity constitute a significant roadblock to enterprises scaling new approaches, they’re not the only one — or more precisely, that roadblock creates another challenge.
The tools that support these modern approaches often begin to lose their effectiveness as organizations attempt to deploy them more broadly within the enterprise. And they struggle for the same reason.
Whether its DevOps, agile, or data science, most vendors built tools to help small teams adopt these new approaches. Moreover, they typically designed their tools to meet a small and specific set of needs.
To be fair, as these approaches emerged, that’s precisely what was needed.
But as organizations look to scale their efforts, the same technical and cultural complexity and rigidity challenges begin to wreak havoc on these tools as they were just not built with them in mind.
While this is beginning to change, many of the tools that support these new approaches cannot deal with the governance challenges, intricate communication, and coordination needs, or provide the consolidated management layer that enterprise organizations will need if they hope to truly scale these efforts.
While having these capabilities will not solve the underlying cultural complexity and rigidity issues, their absence can exacerbate the situation and ensure that organizational efforts to scale these approaches are dead-on-arrival.
Becoming a Culture-First Organization
There’s plenty of talk today about the fact that enterprise organizations need to become cloud-first, mobile-first, cognitive-first or whatever ‘first’ will come next.
When it comes to scaling the early wins found in modern approaches across the enterprise, however, organizations must become culture-first.
These approaches offer enterprises the hope that they can modernize their technology operating model to fight off would-be disruptors and even begin to become disruptive themselves. But doing so requires much more than adopting the approach du jour or buying a new “modern development platform.”
The only sure way to adopt modern approaches and scale them across the organization is to first do the hard work of cultural change. That means being open to changing everything from your operating model to your reporting structure to compensation models.
But more than anything, it means that you must be prepared to do whatever it takes to tear down the silos and change the way your teams see themselves and their roles.
Most importantly, it demands that you craft and sell a new vision for your organization — a vision that everyone can see themselves in, and in which they see no place for the way things have always been.
Founder & Institute Fellow
Charles Araujo is a technology analyst and internationally recognized authority on the Digital Enterprise and Leadership in the Digital Era who advises technology companies and enterprise leaders on how to navigate the transition from the Industrial Age to the Digital Era. Having spent over thirty years in the technology industry, he has been researching Digital Transformation long before it became the uber-buzzword of today, and is now focused on helping Digital Era Leaders prepare themselves and their organizations as the macro trends of the primacy of the customer and the primacy of the algorithm collide, ushering us into what he calls The New Human Age.
Principal Analyst with Intellyx, founder of The Institute for Digital Transformation, author of three books, and most recently the co-founder (with his wife) of The MAPS Institute, he is a sought-after keynote speaker and has been quoted or published in CIO, Time, InformationWeek, CIO Insight, NetworkWorld, Computerworld, USA Today, and Forbes.