9th May 2021
Not Subscribed Yet? Sign up Here!
Digital Transformation is Going Back to the Future
They say that nostalgia isn’t what it used to be. Yet, at several points over the last few weeks, I have found myself looking back to reflect on the lessons from over 25 years in high-tech software delivery and business change. Throughout that time, there have been many situations where I have faced the challenges of technology-fuelled transformation. Recently, I have been asking myself how these experiences relate to the situation today.
Many of us have experienced numerous waves of change where we have helped our organizations to deliver successful products and services in times of uncertainty and volatility. As we work our way through the current digital transformation challenges, three key questions are being asked where we can learn a great deal from past experience:
- How can reorganizing teams around products help increase the flexibility and focus in delivery of digital transformation?
- What are the key steps that help mark progress in the digital transformation journey as organizations mature their capabilities?
- Is it more effective and efficient for success when facing digital disruption to structure individuals in an organization in centralized role-based functional pools or disperse them in cross-functional teams?
These questions were the subject of a recent discussion with a former colleague who is now the chief architect at a major financial services company. Similar to many Large Established Organizations (LEOs), this company is engaged on a major multi-year digital transformation programme. Following their initial introduction of digital technologies to automate core business processes, they are facing the next key phase: A critical shift in business practice and organizational structures to take best advantage of these new digital capabilities.
In his company’s situation, initial success with agile software delivery teams in pilot projects had highlighted the importance of well-integrated teams working on new product releases. The challenge ahead is to adopt this approach in broader contexts. But like most organizations, there was a long history and strong culture of project-based strategy, planning, and delivery. While a shift to tighter team focus around products seemed to be the right way forward, the impacts and implications of such a move remained unclear.
Defining the most appropriate structuring approach for organizations is a classic debate that has been raging for many years, as pointed out to me by my colleague Christine Ashton. She pointed me to a fascinating Harvard Business Review paper from 1968 that studied manufacturing organizations to understand more about the implications of a product vs. function choice in structuring teams. The conclusion, not unsurprisingly, was that “the essential step is identifying the demands of the task confronting the organization”. If the tasks were routine and stable, then a functional approach was a better fit. If the aim was tighter integration to differentiate products or react to dynamic conditions, then a product orientation made more sense.
Over the past 20 years, the importance of team structures and their interactions have been central themes in much of the thinking when scaling agile techniques for LEOs. It has been remarkable in many of my activities to see the impact of Conway’s Law in practice: The structures of the systems we build inevitably bear a strong resemblance to the structures of the teams that built them. For good and for bad. Hence, the consequences of your decisions on team structure are critical. A topic very well addressed in the book by Matthew Skelton and Manuel Pais.
It is a theme that has been equally important when defining a broader view of transformation as organizations mature over time. I have been involved in several recent conversations with organizations involved in digital transformation initiatives that were struggling to align different initiatives so were considering how best to benchmark both progress on their digital journey, and their relative position with respect to other organizations in markets in which they compete. In their eyes, a “maturity model” seems to be the answer.
The idea of “maturity models” is a broad concept that has been widely applied over the past few decades. My personal experiences began with my time at the Software Engineering Institute (SEI) with the Capability Maturity Model Integration (CMMI) approach. This is an improvement framework primarily used in software organizations to assess and improve their effectiveness at scale and over long periods of time. While CMMI captures a rich and deep set of concepts, the basic idea is that 5 levels of maturity describe the key stages in the journey being undertaken. The characteristics at each level imply a set of Improvement strategies and measures of their adoption as the foundation for moving between the stages to increase delivery maturity.
Several organizations have adapted the broad ideas of maturity models to digital technology adoption and transformation. There are interesting examples from Deloitte, BCG, Forrester, Digitopia, and many others. While they differ in many areas, their main ideas are common in assessing the way digital technology initiatives are supported by the changes in attitude, application, and adoption across the affected teams and individuals. Roughly, their multi-step approach to improvement mirrors those seen in earlier efforts such as the CMMI.
However, their use also comes with challenges and criticisms. It starts with questions of clarity, language, and concepts. Something Bertrand Meyer was keen to highlight in his concerns about the CMMI. It is essential these improvement frameworks ensure that they employ some rigour to their thinking and reflect that in the model itself. Something that is too often missing in the new wave of maturity models.
Next, there is a key choice to be made about the unit of assessment: what is being assessed and how that assessment is used. Is the maturity aimed at understanding more about the organization, the teams, the individuals, or some combination? Is the assessment a view into the current state or a guide to future priorities? The CMMI is an organizational assessment framework. In my discussions with Watts Humphrey, the inspiration for many of the key ideas of the CMMI, he always stressed that organizational consistency was his primary concern. Later on he moved to consider individuals and teams via his Personal Software Process and Teams Software Process initiatives.
Finally, it is too often found that early aspirations about improvement and shared values using maturity models devolves to checklists and rules. In an effort to coordinate using the model, managers over generalize the behaviours described and insist that they become mandates for how everyone must operate.
My personal experiences with the CMMI make me wary of the “box-ticking” practices that too often accompany their use. Maturity models bring a useful focus for organizations as they seek to define their strategies and measure their progress. The key, however, is not to treat them as straightjackets that constrain how organizations view their priorities. They are most effective when they guide and support the decisions being made by empowered digital transformation leaders to carry out their difficult task.
In the end, my most important reflection on organizational challenges concerns the need for speed of decision making in times of uncertainty. We have all been caught at times in the “analysis paralysis” that is associated with the search for certainty and consistency in a fast-moving context where decisions must be made without all the facts.
Looking back at those experiences, invariably we made 2 key mistakes; We assumed we would make better decision if we waited for more information, and we considered our perspective on the situation was broader and more holistic than those at the coal face. We were wrong on both counts. Far more progress would have been made if we had prioritized early action over additional debate, organized more dynamically around the needs of the clients as they became better understood, and pushed for the decisions to be taken closer to the action where information was freshest.
Digital Economy Tidbits
The Economy Is (Almost) Back. It Is Looking Different Than It Used To. Link.
One of the big questions we now face is “How will the economy recover after covid?”. The answer seems to be both “quickly” and “unevenly”…
The central reality of the economy in 2021 is that it’s profoundly unequal across sectors, unbalanced in ways that have enormous long-term implications for businesses and workers.
The economy is recovering rapidly, and is on track to reach the levels of overall G.D.P. that would have been expected before anyone had heard of Covid-19. But that masks some extreme shifts in composition of what the United States is producing. That matters both for the businesses on the losing end of those shifts and for their workers, who may need to find their way into the growing sectors.
Big tech profits soar on pandemic boost. Link.
It is worth remembering just how much the profits of the big tech companies have increased over the period of the pandemic. Astounding. Is this a sign of the acceleration of digital transformation…or simply a blip of the historic circumstances of today’s marketplace?