Moving from “leveraging data” in your applications to “leading with data” in your transformation

If you remember any strategy of a company in the last decade, probably had Digital Transformation at its core. This was -still is- a big effort to transform companies into agile, omnichannel, mobile first, 24/7 digital businesses.

If you review strategies from the last years, no matter the industry the company operates in, you will find most of them have data as a key priority. As we discussed in our previous article , there are extremely good reasons for that. However, after several years of having data as a mantra, many companies are realizing that just having data is not enough, as much as just having an ecommerce platform does not transform you into a digital company.

One of the key obstacles we encounter is that data is everywhere in your company, in every application. It might look like, if you modernize your applications, then your data will be automatically addressed in the process and modernized as a result. I like to call this the application-centric view. The reality is just the opposite, your applications cannot be fully modernized unless you are data-centric. Following our ecommerce example, you cannot maximize your ecommerce sales and margin if you do not have visibility of your customer data across the different channels, proper understanding of your stocks across all your systems and predictability of your supply chain. You need data from all these systems (CRMs, ERPs, mainframes, digital channels, etc.) that can be shared, analyzed and actioned upon to fully benefit from your ecommerce platform.

Let’s summarize what a data-centric company does:

• Recognizes the importance of data beyond IT or Reporting or Compliance: data applies to the whole organization and to every employee. As a result, a data-centric company puts intentional and specific focus on data (vs data is everywhere)
• Approaches data holistically across every application, to remove silos and improve data management and knowledge sharing, inside their company and beyond with partners.
• Take evidence-based decisions openly, using more leading vs lagging indicators and create the culture and mechanism to support this approach.

Unless your company was designed directly to be data-centric (do not confuse with native-digital although it could and should go hand in hand) it is not that straight forward to cover the list above. You need a data-led transformation to be a data-driven company that moves from having data in their applications to leading their transformation priorities with data.

Our experience has shown that, as most successful transformations, Data-led transformation takes time, effort and commitment that is better if focalized on three specific areas:

Business Value: Acknowledging this is a long-term program that needs to be driven from the CEO and CxO levels. Providing the adequate funding and stablishing the mechanisms to ensure every dollar you spend has a ROI for your business, combining strategy and agile execution. Determine the KPIs for each business owner to ensure they take an active role in the transformation, using the budget to drive the right outcomes.

Culture: Every transformation requires a new mindset to drive a new culture. The data-led transformation requires your organization understands the value of data. Every manager has to move from “this has always been done in this way” to “based on the data we have” decisions and be incentivized to share their data and knowledge. Every employee needs to understand how to use data (and what is possible out of it) and how they can contribute to the usage of data. A successful data-led transformation empowers every employee to have the right behaviors and tools and implements the processes to achieve it, including automation and AI. You probably need to think about upskilling your employees to do more with data and combine it with the right outside talent and partners in this journey. You also want to make sure at company level that you have the mechanisms in place to track and support the ethical, transparent, and responsible use of your data.

Data & AI Platform: you need the right technology to support your transformation. If you have the business plan, the conviction to pivot, and the budget, now you need the right Data & AI Platform to realize your vision.

Take the example of this financial company, long term Accenture, Avanade and Microsoft client, for decades with the mission statement of staying the “preferred and trusted financial institution” of their customers. To follow their north star of being “customer-centric”, a couple of years ago, they had an ambition to improve their communications, providing more meaningful interactions with their customers and a better marketing ROI. A non-data-centric company would have set up some machine learning algorithms in a SaaS tool to drive some product recommendations for a marketing campaign. Unfortunately, the benefit of this (considerable) effort has over and over proven to be very limited, because the amount of quality data available to use in your models leads to quite generic, poor answers.

As this client was already aware of the limited impact of an independent project, Accenture worked with the C-suite to pivot their company vision from a customer-centric-programs company to a customer-insights-centric one. Once they embraced the idea that to thrive in any area of their business, they need the data to generate the insights, they were ready for the next step of their data-led transformation. The company agreed to create a 3-year company-wide plan with a robust Data Management Practice. They selected Azure to build their customer-centric analytics platform on a modern cloud architecture including 22 Data capabilities and 28 data sources ingested (hundreds of TBs). The C-suit tracks the business value delivered each quarter -with 24 initiatives ongoing- and reskilled and hired 300 employees to use these capabilities. As a result, this financial company has now a data-centric approach that allows them to achieve sustained growth and respond to increased competition. Only for marketing they moved to an inefficient push strategy to an inbound one with operational efficiencies of +15% and 29% of customers qualified for additional benefits.

I am so proud to be part of the Accenture and Avanade family and honored to be part of transformational data-led journeys with this, and so many other great clients. A tough but also a very rewarding journey, as the right technology allow us to realize the business value of the data-led transformation at speed. But for that…I think we need another post!