Baseball is historically rich with data about a player’s in-game performance. Discovering unique metrics and applying deeper level analytics to a player’s performance led to Bill James’ development of Sabermetrics as an empirical analysis methodology.
Though initially his approach was shunned by baseball purists, it has become an integral part of every Club’s player-management approach. “Sabermetricians” use enhanced statistical analysis versus traditional measures to identify and predict a team’s likelihood of success. Criteria such as on-base percentage, slugging percentage and range factor allow for greater predictability of success than the historical indicators of batting average and fielding percentage, for example. This “deeper analysis” approach was fully embraced by the Boston Red Sox, who hired Bill James in 2003. Perhaps it’s no coincidence that the Club has won three World Series since hiring James!
IT Departments rely on their infrastructure management teams to build a foundation that supports a system for their entire organisation. Infrastructure is composed of physical and virtual resources that support the flow, storage, processing and analysis of data. Organisations rely heavily on data and processing needs to support the business. However, the demands of the infrastructure swing wildly to extremes in the matter of minutes driven by a variety of internal and external factors.
Harnessing the insight and leveraging the predictability about these types of demands can help IT teams maneuver through the turbulence. Proper insight allows IT Department Leaders to make better, more proactive decisions regarding their platforms that, in turn, lead to more impactful business decisions.
A winning IT team leverages statistical data to positively impact time and resources
Implementing Predictive Insights and Analytics (PIA), a reporting system that measures real-time user and system activity, enables IT Leaders to empower their teams. PIA is a service that provides meaningful data with relevant information to address pain points and resolve issues, before their business is negatively impacted.
How does PIA work? PIA delivers deep insights into all end-user computing infrastructure components which can identify opportunities to optimise IT systems and highlight cost savings by eliminating inefficiencies in the environment. It automatically monitors the environment in real time to identify problems before they become issues thereby creating a proactive culture (less time consuming than a reactive culture).
In other words, a lack of visibility into your end user experience results in higher unplanned costs. PIA provides the analytical insights and provides recommendations that maximise resource utilisation and reduces the overall infrastructure footprint required to meet your end user expectations.
Guiding your teams “to the playoffs” every season
In Baseball, it’s all about creating the very best lineup (pitching, hitting, fielding) to match up against your competition. Each decision is made based on role specific statistics.
Similarly, PIA provides tailored dashboarding and reporting to ensure each role in IT is provided a view of their “competition” (e.g., compute power, resource drag, etc.) A CIO, an IT Manager or a Support Analyst, all have different sets of statistics required to better improve their decision making. Data that the CIO or Support Analyst can identify with creates their team’s competitive advantage.
Knowledge moves the curve
“There will always be people who are ahead of the curve, and people who are behind the curve. But knowledge moves the curve.”, Bill James.
Predictive Insights and Analytics (PIA) delivers the analysis and knowledge to ensure that IT is optimising its infrastructure. Improving reliability, performance and enhanced user experience keeps the business ahead of the curve and on the path to delivering a solid ROI for the business.
To view dashboard and reporting examples email Insentra on email@example.com or call +61 2 8203 1600
This article was first written by Shane Cook, VP Business Development, and first seen on