How to Modernize Multigenerational IT to Drive Your Business

Despite all the talk of modernization and cloud migration, the multigenerational IT landscape is here to stay. Yet with the right road map and strategic partnerships in place, it is possible to streamline the transition and gain value from data wherever it resides.

Global cloud adoption continues its rapid expansion: IDC forecasts total worldwide spending on public and private cloud services, hardware, and software to surpass $1.3 trillion by 2025. At the same time, however, companies steering toward a hybrid cloud future also have to contend with a multigenerational IT landscape. Often legacy systems impede data-first modernization and the ability to derive value from data assets.

Specifically, the complexity of outdated data architectures means that IT organizations spend more time dealing with hidden challenges and arcane workarounds and less time on innovation and advancing analytics to spark better decision-making. A McKinsey survey found that 10% to 20% of the technology budget earmarked for new products ends up diverted to resolving issues related to technical debt, and the burden is only worsening.

“There’s technical debt associated with the way we did things and the decisions that were made 20 years before, but the thinking is out of sync with today’s reality,” explains Denis Vilfort, director of edge marketing at HPE. “[Technology] fashions come and go, but the decisions made stick around for a long time and you end up with a multigenerational structure that needs care and feeding.”

Without confronting the problem head on, companies limit their ability to accelerate decision velocity and deliver a continuous stream of innovation. In fact, the transformation divide is getting wider as those companies better able to effectively modernize their data estate sprint ahead. Research from KPMG shows that 67% of CEOs feel that their companies are losing ground.

More than 70% of the companies responding to the McKinsey survey believe that their digital transformation efforts are underperforming, either not meeting expectations or not resulting in sustainable change. In comparison, the gains of the companies in the top performance quintile are double those of their competitors, according to McKinsey.

A hard look at multigenerational IT

Here’s the reality of what many IT teams face:

• It’s a siloed and closed world. With data trapped in legacy systems or strewn across multiple public clouds, there is limited visibility across the enterprise data estate. In addition, companies can’t deliver ubiquitous access to all the relevant data needed to derive meaningful business insights, whether that data is internal or available from external sources.

• It’s filled with friction. The reality of multicloud environments is that IT organizations have to contend with multiple vendors and different service-level agreements (SLAs). This creates a decentralized IT infrastructure that’s overly complex and difficult to manage. Without a centralized view of the entire data estate, it’s hard to control costs, drive efficiencies, and deliver the agile backbone so essential for modern digital business.

• Edge is an afterthought. Without a vision and a data architecture for operationalizing data generated at the edge, organizations miss the opportunity for true innovation, whether that’s to optimize customer experiences or to support predictive and proactive product maintenance. This means thinking of infrastructure to accommodate data processing and storage closer to where insights have the greatest impact on decision-making.

One example: the manufacturing sector. According to IDC, 74% of operational data will be acquired, analyzed, and acted on within the factory. In addition, over 75% of edge solutions deployed by manufacturers are either fully managed or comanaged through a services model, enabling greater flexibility and confidence.

“When you’re talking about real-time analytics, you have to kiss a cloud-first strategy goodbye and do a data-first, edge-first strategy,” Vilfort contends. “It’s the third wave of computing — from the data center to cloud to the edge. There are things we can do at the edge we just couldn’t do in the data center.”

Finding a solution to move forward

Few organizations are situated to make a wholesale shift to the new paradigm, given financial and operational constraints. But forward-thinking IT leaders can keep these considerations in mind as they plan for future technology investment:

• Create a road map. Not every system demands modernization. For example, some legacy systems may still be delivering for the business. Allow new projects to drive the shift to streamline the transition and maximize the value of modernization efforts.

• Embrace a new architecture. This means directing compute and storage resources to where data resides, whether that’s close to a network of robots in a factory or X-ray systems in a medical facility. Instead of building out and running the equivalent of mini data centers at every edge location, for example, organizations should look for solutions that can bring cloud-native capabilities to where the data resides — along with a partner that can manage the infrastructure as a service (IaaS).

• Simplify the IT experience. This can be achieved with unified cloud capability for data and applications. The goal is to have a single IT operating model that orchestrates across edges, data centers, colocation facilities, and multiple clouds while delivering the proper data rights, security controls, and governance.

• Choose your partner carefully. A partner offering consultancy services for modernization can accelerate the journey, help identify opportunities for digital transformation, operationalize efforts with proven methodologies and intellectual property (IP), and keep initiatives on track.

• Focus on business outcomes. Partnerships built for this new world should be structured around outcome-based models. With this approach, contracts are designed around specific outcomes — for example, leveraging AI and real-time analytics from plant floor equipment to improve product quality or factory capacity or parsing in-store camera data with intelligence to reduce retail theft.

The bottom line? It’s time for companies to focus on data-first business strategies, not hardware and IT operations. “In a data-first strategy, data is valuable to the business … and outcomes can be quantified in dollars and cents,” Vilfort explains. “Organizations should pay for the outcomes, not the [hardware and networking] gear.”

To learn more about how HPE experts can help address ways to streamline your modernization and data transition to maximize data’s value, check out  https://www.hpe.com/us/en/greenlake/cloud-adoption-framework.html