A point in the Harvard Business Review book, HBR Guide to Data Analytics Basics for Managers, that resonated with me the most was that “organizations become their metrics” and “what you measure is what you manage” because I have seen it play out in organizations that require departments to report on metrics (HBR 2018, 53). For organizations that don’t understand this idea, it can often lead to time-wasting procedures trying to maximize bad metrics.
An example of where I have seen this play out revolved around poorly selected metrics. A new leader was brought in and wanted to setup an organization-wide metrics reporting framework for quarterly reporting. Since most of the organization hadn’t done something like this before, there was a scramble for some departments to create metrics just so they had something to report. There was no over-arching strategy for the use of the metrics, so some departments reported on any data pieces they had. This led to some groups reporting things like time or cost reductions, but some groups unfamiliar with the approach were measuring things like total number of requests received for example.
For a facility management group, total number of requests without breakout as to what the request categories were led to improper focus of activity. Since the only action to be taken from such high-level metrics was to reduce the number of requests, the abilities to make changes were limited. If an HVAC system broke or someone needed an extension cord, the system recorded one request for each issue even though they were vastly different tasks. To prevent the first request, a person would have to ensure proper maintenance and monitoring of an HVAC system. To prevent the other, having someone call or come to the facility person’s desk for a cord instead of making the request in the tracking system was what began to occur. So, while the requests decreased quarter over quarter, the costs associated with the facility management operations weren’t impacted at all and less requests minimized any insights that could be derived from the full dataset in the future.
This is just one example of many I have seen where metrics for reporting were chosen due to the ease of obtaining the data and not around what the data could be used for in terms of actionable insights. When I read that organizations become their metrics, it resonated with me and what I have seen in my career. This guidance tied with ensuring that the proper metrics are chosen really stood out to me. It is important for organizations to understand what their long term vision and goals are, and work backwards to determine what the granular metrics measuring progress to those goals will be. It can be easy to just measure the data you currently have available, but to truly provide continued value creation, measuring the most material aspects of a goal is important.
Author: Logan Callen
Harvard Business Review Press. 2018. HBR Guide to Data Analytics Basics for Managers. Boston: Harvard Business Press.