The data center industry is at the forefront of our new, connected digital world, yet the majority of organizations still struggle to accurately measure operational performance and quantify their investments financially.
This is partly because of an overreliance on inaccurate metrics, baselines, and manual calculations. Many data center management teams still use spreadsheets and rudimentary analytical methods to assess facility efficiency. Predictive modeling has only just emerged as a viable solution to data center energy, capacity, and financial challenges.
The adoption of big data analytics in the data center is being driven by two core business units. The first is operational staff searching for tools that deliver a greater understanding of existing capacity. The second is senior executives – enterprise CIOs and CFOs under greater scrutiny from customers and shareholders. These executives have to demonstrate their control over the company’s multi-million dollar investments that are necessary to maintain competitiveness.
What if we Invest in Big Data?
The pressures facing enterprise executives are many. They face intense regulatory and sustainability demands. They must drive financial and operational accountability for the IT services that underpin business success. They even have to navigate a public relations minefield occupied by “green” organizations that are on the lookout for mismanagement from a corporate social responsibility perspective.
However, ultimately it is the IT department’s responsibility to employ a more philosophical approach to solving these major business challenges. After all, an organization is only as strong as the data infrastructure that houses and serves its corporate information, applications, and connectivity.
More than TCO
Many companies think that answering the question, “How much money are we spending on our data centers?” is enough, but true analysis extends further than simplistic estimations of total cost of ownership. To elevate their competitive position, companies must be able to address successfully a wide variety of scenarios typical to the data center.
Typical scenarios can include the following:
- What if we deploy this brand of uninterruptable power supply?
- What happens to system reliability if we adjust the airflow in this location?
- What will occur if water taxation increases 1 percent every two years for the next decade?
- Should we adopt “free cooling” and how can we make it economically viable?
- How can we prove to investors that our data centers are as financially efficient as possible?
Effective management requires asking the right questions and preventing analyses that are based on incorrect statistical measurements. This challenge is particularly prevalent within the multi-tenant data center sector.
Colocation and cloud providers build their business models around finite considerations. Physical space in a facility is certainly not infinite, nor is the energy or water a data center runs on. And the prices that customers are willing to pay are decreasing on a monthly basis.
For multi-tenant data center operators, the implications of not answering the right questions can negatively affect long-term revenue growth and shareholder value. Until now, most providers could only bide their time and react once changes had occurred in the marketplace. Recently, for example, this has included rapidly falling customer revenues and hardware commoditization.
Big data analytics enables a much more forward-thinking business strategy. The “what-if” questions are similar to those asked by enterprise executives – they revolve around financial scenarios and commercial considerations.
- What happens if we migrate this one customer to another IT hall?
- How are power bills affected by new cooling infrastructure?
- Does this investment deliver a positive financial outcome, or does the initial capital expenditure outweigh operational cost savings in the long term?
- Where in the world should our next facility be constructed?
- What if this subset of customers were moved to a more financially beneficial contract?
With the appropriate big data analytical tools in place, multi-tenant data center operators can proactively model and simulate these questions efficiently and accurately. Organizations can then implement adjustments knowing what the financial consequences will be.
In such a fast-moving, ultra-competitive market, possessing these capabilities becomes essential. Traditionally, enterprise-class facilities always have been a cost, not a revenue generator, but executives need to start considering data centers as valuable business units. With the accountability that big data gives executives, solutions are creating an evolution in the way businesses process and use information that, until recently, was unavailable.
Years of historic environmental, energy, climate, IT, and financial data are being unlocked thanks to the power of new analytical tools, strategic initiatives, and board-level recognition that data centers are some of the most valuable assets in a company’s portfolio.
Richard Jenkins is Senior Vice President of Global Marketing at Romonet.
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