Subscribe
For sports fans this is an exciting time of the year with both the NBA and NHL finals taking place simultaneously.
There’s added excitement this year with the renewal of the classic Lakers and Celtics rivalry and the Chicago Blackhawks looking for their first Stanley Cup championship since 1961.
As in sports, companies and internal departments need to identify key performance metrics which translate to success in their industry.
Just as analysts review a company’s balance sheet and operational metrics, many fans and sports analysts refer to team and player statistics in order to support their predictions of who will win their respective league championship. In the NBA finals, they’ll be citing each team’s shooting percentage from the free throw line and the field as a key performance indicator. In hockey, there are the obvious statistics of number of power play goals and goals against average. But this year, analyst have cited the unusual statistic of Chicago’s offense scoring 11 goals with 10 different players as a key indicator of its success through game 3 of the championship series. The implication is identifying the Stanley Cup series specific statistics over and above the commonly followed season statistics in order for either team to make adjustments to win the Cup.
Many organizations today do a terrific job at measuring their own teams’ statistics – take the airline industry for example: they measure the use of number of seat miles for which the company earned revenues. What’s more difficult is identifying meaningful performance indicators at the departmental or individual level within an organization? Effective identification and translation of organizational specifics makes an executive’s job easier when identifying and adjusting to trends, defending team budgets, identifying savings opportunities, and even negotiating contracts. This is especially true within an IT organization.
One of my favorite Information technology metrics which typically does not appear on the company’s balance sheet or in the annual report but translates into effective IT performance are the metrics related to desktop or PC support. I like these metrics because Joe the worker at Company X probably does not care anything about IT metrics. But Joe and his peers know who to call for problems with their PC’s. You know – the “IT guy” who the department takes out to an appreciation lunch once or twice a year. Keep Joe and his peers happy and that will translate to good scores for IT support. Remotely identifying and correcting Joe’s PC problems at the help desk is almost always the most efficient and cost effective way to provide desktop support. Therefore statistics such as average time to answer and mean time to repair (MTTR) are often cited as an accurate performance measurement of the desktop support unit. These statistics have further downstream implications for identifying the desktop to technician ratios or the number of technicians required to be in the field when problems cannot be solved remotely or over the phone with an agent. Organizations which typically resolve most incidents remotely with an agent do not need as many field technicians and therefore have high desktop to field technician ratio’s and are considered the most cost efficient.
But just as the Lakers, Celtics, Blackhawks and Flyers will be identifying opportunities and adjustments based upon shot percentages and other common game time metrics, an organization must know how to translate their metrics into performance-improving activities. Although the Flyers have allowed goals by 10 different players after three games, they have been able to hold the Blackhawks top scorers this season to just one goal in the finals. So in some respect, part of the Flyers game plan may be working in shutting down the opposing team’s top scorers and the high number of individual goals per Blackhawk player is a positive metric.
Using the same analogy, there may be reasons why an IT organization has metrics which are out of line with industry standards and those reasons need to be well understood to justify costs. In the desktop support example cited above, a company may require higher PC to technician ratios due to Joe’s high availability requirements. For example, our friend Joe is an order taker on a trading floor and does not have the time to call the help desk and work with an agent to solve problems with his PC while the markets are open. The same dynamic is also seen in the healthcare industry within clinical environments, where nurses and doctors are focused on treating patients and do not have the bandwidth to diagnose problems accessing automated medical records from PC’s. In these environments, it would obviously be acceptable to experience higher desktop to field support ratio’s to insure key functions within the company have highly available systems and support. Understanding these dynamics is critical when performing organizational benchmarking activities and considering out source opportunities. With regard to outsourcing, you’ll want to understand how a supplier is proposing to achieve savings. Are they proposing to increase the number of PC’s a technician supports from 250 to 500 devices? If their model is predicated by resolving more calls remotely at the help desk you’ll want to closely examine the impact to your organization. Having a deep understanding of your metrics will allow you to better negotiate support costs within your company and negotiate actionable savings strategies offered by department heads and suppliers.
The challenge is to drive meaningful measurements to all levels within your organization. Ask your management chain to identify metrics which translate to their group’s success. Then ask them why the metrics are meaningful and actionable and what needs to be done to improve the scores. I would also suggest that if the measurements are not actionable then they are probably not the right performance indicators to be tracking.
For those deep thinkers out there, I hope these insights will not cause you to become distracted with thoughts of your company’s metrics while watching the NBA and NHL finals.
For those of you wondering, Blackhawks in six games with Kane becoming the scoring leader and Lakers in five by taking advantage of Celtic fouls and a higher free throw percentage.