IT Leadership as a Data-First Change Agent

The importance of data-driven insights may dominate C-level discussions, but evolving IT culture and business workflows that can successfully harness that data is less about talk and more about iterative action.

The good news: IT leaders are well positioned to play that role. But to serve as effective change agents, CIOs and IT leaders need to marshal the right technology investments while resetting culture and processes to break down silos. They must also promote data as a shared business asset with value to drive agility and profitability.

Most organizations are still struggling to fully leverage data assets for sustainable business advantage. In a recent IDG/HPE survey, fewer than half of the respondents reported that they were using data strategically (49%) and the rest said they were leveraging data tactically at best. Companies are capitalizing on only about half (49%) of their data sets to derive direct business value, and 34% feel they are falling short of strategic data-related goals.

What’s more, the uphill battle typically hinges on changing culture to embrace a data-first mentality. According to NewVantage Partners’ “Big Data and AI Executive Survey 2021,” only 24% of the respondents have successfully forged a data culture or created a data-driven organization (also 24%).

“By nature, organizations create silos based on line-of-business needs and lack understanding of how to unlock the trapped value of data sitting inside legacy systems,” says Rocco Lavista, worldwide vice president for HPE GreenLake sales and go-to-market. “IT’s goal is to be the change agent that can knock down these silos, effectively unleashing the value of data from the edge to cloud.”

Data champion to the rescue

Today, a common operating model for data starts with a particular business stakeholder such as the CFO or a marketing lead initiating a specific request. An analytics expert creates and curates the data that that person believes is necessary to answer the question and passes along the resulting insight or recommendation to that business owner.

The problem? Analytics experts don’t always fully understand the business problem or what the client is asking for — and they may not have access to all necessary data sets or data that could contribute to a better answer. That same ineffective process repeats itself when new questions arise or for subsequent follow-up, which detracts from delivering timely or accurate insights.

Consider what happens when you flip the model and embrace data-driven modernization. With the right technology platform, architecture, and process change, IT leaders can knock down data silos and give analytics experts the tools to create a digital data catalog that enables business users to use self-service for what they need, when they need it, and in an automated and user-friendly way. “It’s about making integrated and real-time data available for faster, better-informed decisions while letting analytics experts engage in innovating for the business,” Lavista says.

To champion this kind of data-first modernization, IT leaders will need to embrace five basic imperatives:

1. Data is a core asset that the company, not a public cloud vendor, should control.
2. Data is everywhere and must be accessible at digital speeds from its native location, regardless of how that changes over time. Moreover, movement of data must be frictionless.
3. Data has rights and sovereignty.
4. IT leaders have the freedom to choose the right location for data and workloads but must pay attention to architecture if they want to harness data for insights.
5. Leadership must embrace a unified operating model to drive outcomes and agility.

Using those principles as a guidepost, IT leaders can evolve culture and processes, starting with the formulation of a solid data strategy that maps to core business objectives and KPIs.

Rather than aiming for a big bang approach that tackles end-to-end business process change, for example, organizations should pursue more iterative tactics. They need to identify areas where quick wins are possible and then systematically communicate those achievements to showcase the tangible benefits of a data-first business approach. They must also build trust and generate enthusiasm among business stakeholders for the requisite organizational and cultural change.

Value stream mapping can be an effective tool for redesigning end-to-end business processes, including determining potential gaps or defining which data sets need to be enriched to provide better insights for the business. “By deploying small wins with better business data insights, you eventually amass to what will be a bigger win,” Lavista says. “With a big bang approach, the puck is moved two or three times within the timeframe … and nine times out of 10, you probably don’t get to the end goal.”

The HPE GreenLake advantage

Along with using proven change management tactics, IT leaders need to align with the right platform and partner to advance a data-first business agenda. The HPE GreenLake edge-to-cloud platform can power data modernization, by unifying, scaling, securing, and enabling data sets to be consumable, with context, across the greater enterprise.

The HPE GreenLake edge-to-cloud platform combines enterprise-grade controls delivered across a hybrid multicloud landscape. A pay-per-use as-a-service model that spans data centers, cloud, and edge helps foster agility. This enables organizations to accelerate innovation, deliver compelling experiences, and achieve superior outcomes without the complexity or limitations of traditional IT infrastructure and historical up-front purchasing practices.

At the same time, HPE GreenLake for ML Ops accelerates analytics and shortens time-to-insights through support of frictionless data movement, ensuring that data is universally accessible no matter where it resides. Data is processed and analyzed from every edge environment across the multicloud landscape in a safe and secure way, with the simplicity of a cloud experience. As a result, organizations can empower all corners of the business with insights on demand, at any scale, in any location.

Automation is another pillar of a modern, data-first business, and the HPE GreenLake edge-to-cloud platform delivers with policy-based automation that moves organizations closer to the concept of a data analytics factory. HPE’s full breadth of technology, services, and expertise and an extensive software vendor ecosystem bring IT and business together to tackle today’s data challenges, paving the way for the next wave of digital transformation and for data-first business success.

Despite the power of technology, it takes more than fancy tools to solve for data-first business. “Organizations have to get the culture and operating model part of this right and then deploy the technology and tools that support what you establish,” Lavista says. “There’s no silver bullet for this — do not get distracted by technology tools, but stay focused on the data operating model.”

To learn more, go to https://www.hpe.com/us/en/greenlake/ai-ml-analytics.html.