Generating Business Value from Data on Enterprise IT Usage

Generating Business Value from Data on Enterprise IT Usage

If you listen to the hype, the days of the mainframe computer are numbered, with the technology increasingly eclipsed by hyperscale cloud computing alternatives. In reality, this 60-year old technology continues to be the mainstay of enterprise computing, with 70% of Fortune 500 companies trusting their critical operations to mainframe computing systems. 

However, the computing power delivered by mainframes does not come cheap, and the businesses that use them typically spend tens of millions of dollars each year on running, using, and maintaining these systems. 

Controlling these costs has historically been a challenge. Opaque pricing, convoluted fee calculations, and the sheer complexity of the applications running on enterprise mainframes made mainframe systems something of a black box, with IT teams having no way of mapping systemic inefficiencies or wasted resources.  

Shining a light on mainframe computing usage

In recent years things have improved somewhat. The technology industry has made progress with solutions that can manage and optimise the performance of mainframe systems in line with the constraints of internal financial and human resources. However, with so many operations drawing on mainframe resources, it can still be difficult to track the impact of specific operational activities. 

Fortunately, this state of affairs is due to change. Advances in enterprise data management mean that enterprises can now pull information from a wide variety of sources – such as financial information, logistics data, or marketing analytics – to understand how specific operations and projects affect the use, performance, and fees of mainframe resources. By collecting, enriching, and exposing data that was previously hidden across disparate IT systems, businesses can now achieve maximum impact with their IT spend. 

The impact of mainframe data

There are a large number of analytical use cases for this mainframe observability data including identifying bottlenecks or inefficiencies in systems, tracking how different projects or operations affect mainframe usage and associated costs, tracking consumption, capping usage, and predicting future needs. The approach also enables transparent tracking, observation, and reporting of critical data to meet regulatory requirements and ensure a secure and accountable IT environment.

To understand what this looks like in the real world, a government agency might use mainframe observability data to track the usage and performance of its mainframe-based database systems. This data would prove valuable in productive capacity planning and would help ensure uninterrupted access to critical public services for the community it serves. 

Similarly, an insurance company could use mainframe observability insights to assess the impact of new policy management software on system performance. This helps in ensuring that the mainframe can handle the increased workload without affecting the user experience.

Digital marketing is another illustrative use case. When measuring the return on investment of a digital marketing campaign, businesses are empowered to take data from Google Analytics and other martech software to quantify the mainframe computing resources used to achieve the campaign goals. Armed with this insight they can then better control costs in future campaigns.

Identifying the right data platform

In short, advances in enterprise data management have overcome key challenges that have stood in the way of mainframe resource optimization: the fact that data is typically scattered across numerous infrastructures – some on-premises, some on cloud – and applications. Enterprises looking to improve the cost and performance of their mainframe systems should look for solutions that provide the following:

  • Complete data integration. Businesses must be able to integrate mainframe data with all other data on the usage of IT resources to achieve a complete view of activity across IT infrastructure – limiting the number of products and processes to manage
  • Ease of use. Given the increasing pace of business, IT cannot be a bottleneck to optimizing mainframe performance. Look for data platforms that enable non-technical experts to easily configure and customize the tools to get to the reports and insights they need.
  • Optimization tools. The best solutions enable data retention and compression that limits the footprint of data within the mainframe. 
  • Business and technical focus. Businesses need both a commercial and technical view of mainframe usage to make the best decisions on resource utilization. 

Mainframes have been a core part of enterprise computing for decades, and they still have an important role to play. By adopting modern approaches to enterprise data management, organizations can better observe, manage, and optimize the performance of mainframe systems to meet operational requirements. Armed with the right approach to optimization and cost controls, the best days of the mainframe may well lie ahead of us. 

About the Author

With his extensive experience transitioning from Sales Director to CCO into the intricacies of the packaging industry, Stefano Pilotto brings a wealth of expertise to Zetaly. His proven track record in sales leadership positions and strategic business management across multiple continents has positioned him perfectly to spearhead the sales team’s efforts on a global scale and drive revenue growth for Zetaly. His comprehensive industry knowledge and leadership acumen will be instrumental in expanding Zetaly’s market presence and fostering valuable customer relationships across diverse regions.

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