The ongoing digital revolution is exciting, but it’s not exactly firing on all cylinders. Technology innovations, such as blockchain, the internet of things (IoT), cloud computing and machine learning, are impressive, but innovations in technology management – vital for realizing tangible business outcomes from emerging technologies – are grossly lagging. In my previous post, “The Weakest Link in Digital Transformation,” I explained why the multitrillion-dollar enterprise IT industry cannot evolve for the future from a retrofit of half-century-old IT management practices with relics of the industrial age. Today, we will explore why much-needed technology management innovations are so hard to come by in the digital age.
If you have been observing digital transformation initiatives across financial services companies over the past few years, you have probably noticed an implementation pattern that becomes progressively sophisticated, with increases in the completeness of vision and the ability to execute a digital transformation program. Figure 1 illustrates this phenomenon below.
Before we dive into the details, let’s align on key definitions:
- Completeness of vision refers to how well digital ambitions, goals and commitments are articulated by the leadership and embraced by the enterprise.
- Ability to execute implies an optimized initiative portfolio and structured program, a confident workforce, and a goal- and KPI-driven performance management system.
- Implementation approach relates to decisions about scope, sequence and expected program outcomes.
Digital programs are most productive when the completeness of vision and the execution ability are in balance. This balance is shown here in Figure 1 by the diagonal blue line.
Most digital transformation implementation approaches fit into one of the following five categories (illustrated in Figure 2, below):
1. Incremental: This approach refers to locally run digital experiments or grassroots initiatives such as research activities, proof of concept projects or pilot implementations. Local teams feel confident about their ability to execute, but they can’t secure an executive mandate to proceed with their ambitious plans. Most agile development, DevOps activities fall into this category. Key characteristics are uncertain executive support, low appetite for risk, bias for short-term/quick hits, and an ever-evolving definition of success.
2. Wholesale: This is the case when a whole function or organization is targeted for transformation at once, e.g., migration of thousands of developers from waterfall to agile in a single swoop. It is driven by a top-down executive mandate, which is often not well understood or not embraced by the rest of the organization. Expectations run high, while patience for impact is low, and implementation risks are largely unknown.
3. Greenfield: This is the tamed version of the wholesale approach described above. The primary objective is to create a new digital function independent of its traditional equivalent – a separate leader, organization, budget, processes, tools, etc. A good example is a software-defined data center initiative at a company like the Bank of America (a greenfield project). Such initiatives are often C-suite-sponsored, well-funded and well-tolerated (can’t say embraced yet) by the traditional part of the enterprise. Time-to-market is a primary concern, but often there are no plans for migrating legacy systems. The business is consulted, but action remains on the IT side – in other words, it’s an IT problem.
4. Capability: What differentiates this approach from greenfield is the focus on capabilities vs. functions, outcomes vs. outputs, and total-enterprise vs. digital-only, e.g., the Starbucks way of going digital. Each capability serves a specific purpose within the enterprise vision, and comes with a formalized C-suite commitment to outcomes, a strong customer engagement, a long-term value-optimized road map, and a persistent team per capability.
5. Lean: Here, the capability build-out is considered table stakes, and emphasis is put on comprehensive, systematic and continued improvement of those capabilities through innovations at the underlying operating model and culture. Best executed at digital bellwether companies like Amazon, Google, Netflix.
Using a real-life example, we will now explore how traditional enterprises land on their chosen implementation approach for their digital transformation endeavors. This case is about a leading insurer and investment management company, which was striving for a significant revenue growth through business insights enabled by advanced analytics. The COO sponsored an enterprise analytics capability program, and obtained the C-suite’s buy-in. Although the technical requirements were successfully met, the business units never fully used the capability, and expected revenue growth didn’t materialize. What went wrong?
Let’s go back to Figure 1, where Point C represents the current digital transformation maturity of the company and Point D is the maturity that the company believed it required to achieve the desired outcomes. At the onset of the program, the leadership determined accurately that they lacked analytics expertise and experience in running digital implementation projects – in other words, there was an execution gap.
Although C-suite support was obtained, not all business unit leaders were on board with the idea of sharing data across organizational silos. Also, the enterprise IT organization was not involved in the planning and design of the program – in other words, there was a vision gap.
In addition to these, the company mistakenly assumed that building a shared service with all the necessary people, processes and tools would be adequate to realize business outcomes. They never properly appreciated the need for enhancing the operating model and culture. Consequently, instead of landing at Point 2, they ended up at Point 1, which gave them a working IT capability, but not the business outcomes they asked for – in other words, there was an aspiration gap.
A key takeaway of this story is that when leadership won’t resolve the vision gap, the rest of the enterprise cannot appreciate the true magnitude of the execution gap – incrementalism, best-effort governance, and bias for outputs vs. outcomes flourish. The teams succeed in building new capabilities, but overlook the softer side of the digital transformation, namely the operating model innovations and culture change. Consequently, expected business outcomes are either delayed or do not materialize at all, which we call the aspiration gap of digital transformation.
The vision gap, which is one of the key culprits for the aspiration gap, is systematically overlooked at many digital transformation programs because of the following reasons:
- The solution spans multiple organizational and functional silos, and it requires substantial political capital and leadership stamina.
- Evidence of the impact of the vision gap on business outcomes is hard to demonstrate.
- Managers are leery about committing to outcomes without clarity on the vision.
The overarching question is how to get ahead of the curve in addressing the “aspiration gap” of digital transformation. I will explore this topic in a future post.
This article was written by Hakan Altintepe from CIO and was legally licensed through the NewsCred publisher network.