How much money is your organization leaving on the table by not being more effective at leveraging data and analytics to power your business?
This question is becoming more and more relevant for all organizations of all sizes in all industries as AI / ML capabilities become more widely available. And nothing highlights the costs of not becoming more effective at leveraging data and analytics to power your business models then a recent study by Kearney titled “The impact of analytics in 2020”.
There are lots of great insights in this report. One of my favorites is the Analytics Impact Index which shows the “potential percentage profitability gap” of Laggards, Followers, and Explorers vis-à-vis Analytics Leaders (see Figure 1)!
Figure 1: Analytics Impact Index by Kearney
Figure 1 states that from a potential profitability perspective:
Hey folks, this is a critical observation! The Kearney research puts a potential cost on being an analytics laggard (or follower or explorer), and the money being left on the table is significant. The Kearney research highlights the business-critical nature of the question:
How effective is your organization at leveraging data and analytics to power your business models?
This is the same question that asked when I released the Big Data Business Model Maturity Index in November 27, 2012. I developed the Big Data Business Model Maturity Index to help organizations understand the realm of the possible for becoming more effective at leveraging data and analytics to power their business models. The Big Data Business Model Maturity Index served two purposes:
I refreshed the Big Data Business Model Maturity Index to reflect the changes in advanced analytics (and the integration of design thinking) since I first created the chart. I’ve renamed the chart “Data & Analytics Business Maturity Index” to reflect that the business challenge is now more focused on the integration of data and analytics (not just Big Data) with the business to deliver measurable, material, and relevant business value (see Figure 2).
Figure 2: Data & Analytics Business Maturity Index
Unfortunately, the Kearney research was a little light on explaining the differences between Laggards, Followers, Explorers, and Leaders phases, and in providing a roadmap for navigating from one phase to the next. So, let’s expand on the characteristics of these phases, and provide a roadmap, using my 5-phase of Data & Analytics Business Maturity Index.
To become more effective at leveraging data and analytics to power your business, we need a definition of the 5 phases of the Data & Analytics Business Maturity Index so that you can 1) determine where you sit vis-à-vis best-in-class data and analytics organizations and 2) can determine the realm of what’s possible in leveraging data and analytics to power your business models.
Note #1: Phase 4 this is NOT “Data Monetization” (which infers a focus on selling one’s data). Instead, Phase 4 is titled “Insights Monetization” which is where organizations are focused on exploiting the unique economic characteristics of data and analytics to derive and drive new sources of customer, product, and operational value.
Note #2: I am contemplating changing Phase 5 from Digital Transformation to Cultural Transformation or Cultural Empowerment for two reasons.
Now that we have defined the characteristics of the 5 phases of the Data & Analytics Business Maturity Index, the next step is to provide a roadmap for how organizations can navigate from one phase to the next. And while Data & Analytics Business Maturity Index in Figure 3 is sort of an eye chart, it is critical to understand the foundational characteristics of each phase in advancing to the next phase.
Figure 3: Data & Analytics Business Maturity Index Roadmap (version 2.0)
What I found interesting in Figure 3 is how the importance of Data Management and Analytic Capabilities – which are critical in the early phases of the Data & Analytics Maturity Index – are replaced in importance by Business Alignment (think Data Monetization) and Culture (think Empowerment). I think this happens for several reasons:
Ultimately, it is Business Alignment (and the ability to monetize insight) and Culture (and the empowerment of individuals and teams to create new sources of value) that separates Laggards, Explorers, and Followers from Leaders.
The Kearney study made it pretty clear what it is costing organizations to be Laggards (as well as Followers and Explorers) in analytics. It truly is leaving money on the table.
And the Data & Analytics Business Maturity Index provides a benchmark to not only to measure how effective your organization is at leveraging data and analytics to power your business, but also provides a roadmap for how your organization can become more effective. But the market leading organizations know that becoming more effective at leveraging data and analytics goes well beyond just data and analytics and requires driving close collaboration with the business stakeholders (Insights Monetization) and creating a culture that is prepared for the continuously-learning and adapting AI-Human interface that creates an organization that is prepared for any transformational situation (Digital or Cultural Transformation).
Seems like a pretty straight-forward way to make more money…