This article was written by Marjorie Freeman.
A data strategy is a plan of action to manage an organization’s data assets across its technology, processes, and people. In practice, that entails understanding how data is generated, where and why it is consumed, and how its use helps organizations achieve strategic objectives.
On Metis Strategy’s Technovation podcast, Peter High has interviewed many global, digital-forward CIOs about their data strategies. Below are insights from those leaders about how companies can use enterprise data assets to their fullest potential.
Tie data to business outcomes
Artificial intelligence has been top of mind for many organizations, even more so in 2023 with the rise of ChatGPT and increased discussion around generative AI. This has prompted a multitude of conversations around AI’s core facet: data, and how it can drive the business forward.
During the February 2023 Metis Strategy Digital Symposium, Krzystof Soltan, the Chief Information Officer of Vulcan Materials Company, and Anupam Khare, the Chief Information Officer of Oshkosh Corporation, shared their experiences building data strategy into complex, scaled organizations.
At Oshkosh, Khare leads with the question: “How do we extract financial value from data by bringing people and data together?” The company is working to become what Khare calls a predictable enterprise, using four fundamental principles to guide the journey:
- Start with a value-first approach. How can leaders leverage a data strategy to extract maximum value from data and clearly measure outcomes?
- Engage people at every level. Who is using data analytics at the associate level, the mid-management level, and the executive/board-level, and how can they be aligned?
- Create a single, consistent technology stack. While it takes time to align technology across the enterprise, it is important to have a relatively standard set of infrastructure and tools.
- Take a use case-centric, bottom-up approach. Oshkosh focused on data and analytics use cases rather than formulating a grand strategy from the top. “Business leaders are saying, ‘these are the six or seven major problems which I want to solve through analytics,’” Khare said.
For Vulcan Materials, data strategy is linked to the organization’s technology strategy. “It always comes back to business value, the time to value, how fast we are able to provide the insights” Soltan said. Vulcan Materials’ looks to the following principles to guide its data and analytics work:
- Speed and time to value. How long does it take to deliver measurable business outcomes?
- Ease of access and use of information and data. Is data available in real-time, hourly, daily, monthly? Understand business needs to make strategic decisions about data availability.
- Get to predictive analytics. While it’s important to use data to understand the past, the company is focused on using data to figure out where it needs to focus to propel the business forward.
- Work toward a standard technology stack. “Do we have a standard set of tools, or do we have too many?” Soltan said. “How do we think about that and rationalize it?”
Both Khare and Soltan’s stories underscore the need to tie data strategy to business value, work toward a common tech stack, and engage people at every level of the organization in the data journey.
Develop a strong data governance plan
OneDigital, which provides customizable and cost-effective HR solutions to organizations and their workforces, acquires around 30 organizations per year. This is no easy feat, but CIO Marcia Calleja-Matsko strives to create a seamless experience for every organization that is onboarded.
When acquiring a new organization, especially one in a different vertical or industry, it is important to ensure there is a consistent record across multiple platforms, Calleja-Matsko says. Cue the single source of truth, or what she calls the “golden record.” Once that record has been created, it must be maintained.
Over the years, Calleja-Matsko has been working to build OneDigital’s data strategy in three key ways:
- Focus on data governance. You can have a consistent data record across multiple platforms and the right roles in place to use that data, but successful execution depends on governance: policies and controls to ensure data remains clean and consistent and is handled in a compliant fashion, no matter how or where it’s ingested.
- Build consistency across platforms. As part of the governance practice, the company’s product teams work to ensure data is consistent across the platforms on which it resides. Good data hygiene helps establish data integrity, as well as greater safety from human error and cyberthreats.
- Collaborate to maintain that consistency. New acquisitions means new technologies that need to be integrated into OneDigital’s portfolio and require close collaboration between IT and the rest of the business. Calleja-Matsko works closely with OneDigital’s product chief to support and scale existing technologies while also looking to the future, ensuring consistent data and tooling and the presence of data stewards who can provide ongoing support.
If data is the new oil and speed is the currency of business, then data governance is the link that fuses the two. For more, see Michael Bertha’s commentary: Data Strategy at the Speed of Business.
Drive data literacy across the enterprise
CIOs play an instrumental role in creating a common language around data and making sure teams across the enterprise have the tools and concepts they need to harness data effectively. To develop this data literacy, many organizations have built enterprise-wide curriculums and training resources.
Monica Caldas, the CIO of Liberty Mutual, which has its own professional development training programs, including one specifically geared toward executives, said it well:
“Technology is everybody’s responsibility these days in terms of understanding what it can do. … Everyone that sits around the table needs to be beyond, ‘How do I click this?’ and [be] somewhat well versed [in topics like] what can an API do, and why does that matter.”
Many organizations have launched digital academies to train employees on digital skills, including technology and data literacy. In 2019, for example, Toyota launched an academy to knock down the invisible wall often found between IT and the business and give end users greater knowledge of the software they use every day. “The idea was to not just train IT, but everyone across the organization.” said then Chief Innovation, Strategy and Digital Officer, Vipin Gupta. The approach has empowered associates across the business to truly understand how to capitalize on the tools, data, and processes at their disposal.
Data literacy is also key to enabling citizen development, an approach that encourages those outside IT to contribute to software development, often via low-code/no-code tools. Paired with increased data literacy, this can make it easier for teams across organizations to apply data and analytics to their work and accelerate time to insight.
Chief Information and Digitization Officer of Reckitt Benckiser Group, Filippo Catalano encourages executives to create opportunities for properly governed self-service data access:
You want to also make sure that, as much as possible, everybody in the company becomes a data scientist. … Get out of the way so you can unleash creativity, empower people everywhere in the organization to do what they need to do on data and analytics, but also to do it on the right platforms so that things are done in a fair way, but also in a safe way.
CIOs, CDIOs, and CDOs are in incredible positions to influence the change they’d like to see within their organizations. Directly engaging individuals in the company’s data journey through hands-on learning opportunities can not only build knowledge and morale, but also can catalyze new competitive advantages.
Tell a compelling story
Any successful data strategy needs a compelling, ambitious vision and a clear path to success that resonates across an organization. CIOs, then, need skillful storytelling to get buy-in from multiple stakeholders and create forward momentum.
Telling the story effectively means, once again, putting business outcomes front and center. “I can talk all day about ‘hey, you should have data governance and you should think about a data lake or a single view of the customer,’” said Dak Liyanearachchi, Head of Data and Technology at NRG Energy. “All of those are really interesting, but what does it really mean to the organization?”
One useful move includes thinking about data as an enterprise asset that requires strong partnership across every part of the business. While companies can notch small wins leveraging data within silos, the real benefit comes when that great work logically connects across the organization.
“If you think about connecting the dots across the value chain, that’s where you start to see some significant business opportunities,” Liyanearachchi said. When that happens, “the value you bring multiplies at a faster rate.”