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The Data Economy: Improving Data Literacy

The Data Economyis a video podcast series about leaders who use data to make positive impacts on their business, customers, and the world. To see all current episodes, explore the podcast episodes library below.

A strong data-driven culture is the latest non-negotiable for organizations that want to put their data to work and stop relying on gut decisions and guesswork. 

In the year ahead, you’re going to hear more about the steps many organizations are taking to make data-driven decision-making core to executing company plans. Shy Chalakudi, Head of Enterprise Data Analytics and Digital Technology at Hewlett Packard Enterprise (HPE), is ahead of the pack, helping instill the data literacy and data focus needed to make data-led decisions ubiquitous at the 59,000-person company. 

Shy was a recent guest on The Data Economy CXO podcast, presented by Redis and hosted by Michael Krigsman of CXOTalk. She discusses the importance of embedding data into every aspect of an organization, the imperative of managing data effectively, and the critical role data is playing in HPE’s digital transformation. 

In the conversation, Shy’s passion for a data-driven future shines through when she declares that “data is going to become a universal language,” with data being what’s “going to let us communicate with each other and the machines, together in one common language.” For HPE, this means collecting zettabytes of telemetry data from the systems and devices it sells and using this data to improve customer experiences and its products.

Shy has a clear message for CIOs tasked with digital transformation: Becoming a data-driven organization is essential to creating new business opportunities, improving customer satisfaction, and addressing new marketing opportunities. For HPE, as in many large companies, operating in a data-driven way starts by knowing the customer and customer 360 architectures that help centralize data and create a single version of the customer’s journey and activities. Companies in financial services and retail should have customer data initiatives at the top of their priority list.   

Shy oversees all aspects of global data initiatives at HPE, a Fortune 150 business information technology company known for its cloud and infrastructure services. Her team’s charter is to drive a data-first modernization for the company, which includes creating a unified data source so that all aspects of digital transformation are rooted in data. 

“My team members live and breathe to ensure that we create a sophisticated, automated, simplified view of data that can be consumed by both internal and external customers,” Shy explains.

Knowing when to tap real-time data

Among the focal points of Shy’s organization is data management—handling the governance of everything from data lineage, data profiling, data quality, and beyond. Her team’s work supports HPE’s efforts of changing its billing pattern from a monthly or yearly subscription to usage-based billing. Shy notes that “Data is at the front and center because you must know your customer and know what solution they are looking for in order to provide a customized, personalized service.”

Real-time data is important when you want to respond to your customers quickly, Shy says. Indeed, when you have access to real-time customer data, you can make smarter, faster decisions that can allow you to stand out from your competitors. When you can make decisions more quickly, you can also make more accurate predictions through real-time analytics and decision capabilities. 

The importance of a data literacy program

Any IT leader who has ever led any aspect of data transformation knows that collecting and delivering the data is only half the battle. If stakeholders aren’t using the data, then the effort falls flat. Shy’s team is working to avoid this adoption pitfall by embedding a data culture in HPE. 

In the podcast, Shy describes the model HPE is using to spread data literacy throughout the massive enterprise, noting that “every consumer of data has to be data literate in order for it to be successful.” At HPE that means every business organization has a data leader who is a senior leader in the organization responsible for supplying answers to key questions such as “What data do I need to run my business? What data am I missing that would help me push my business further?”

Two things don’t surprise me about Shy’s story: First, she emphasizes getting the architecture, DataOps, and data governance in place before seeking machine learning and AI results. IT must be able to scale the data layer in hybrid cloud architectures automatically. “We think that machine learning and artificial intelligence are going to solve all of our problems,” Shy says.  “Trust me, I am a doctoral student and wrote a thesis on AI/ML. I value it very much, but I think it’s important to understand that it is garbage in, garbage out.”

Second, Shy has the benefit of having HPE’s CEO champion the company’s data-driven efforts as it pivots its business model to deliver solutions, personalize services, and transform to a subscription business model. The CEO’s direction sets a strategy, mission, and culture change that helps Shy drive new ways of working.

And while the top-down support provides air cover for Shy’s team to bring data literacy to each business unit, it doesn’t stop there. In the podcast, Shy discusses the important roles that “data stewards” and “data custodians” play in governing and managing data and ensuring it meets the needs of business partners. 

Developing a data literacy program is critical for building a data-driven culture. You can collect and distribute all the data you want, but if your colleagues don’t have the right skills to use data in their roles and draw insights from it, then your efforts will only take you so far. As Shy puts it: “We all have to become data literate in order to survive today—in any industry.” 

Please tune in to the podcast to hear more of Shy’s insights on the architectures and culture that enable HPE to process zettabytes of data while centralizing data and knowledge about its customers.

Watch more episodes of The Data Economy podcast.