One must focus on measures that their team has the power to influence instead of those can be tracked but not controlled.
When I attempted to follow up with my son about the preparations for his exams and the measures he was taking to study, he once retorted that I shouldn’t scrutinize every minute detail of his day, but instead focus on the actual goal, which was to secure a good score in the exams.
His words made me reflect on my work as a manger – of people primarily, and all that it included, from to-do lists and Operations reviews to daily team huddles and meetings with CEO. One “follows up with” (read: scrutinizes) a team that is perpetually overwhelmed with urgent, need-a-solution-now issues (critical payments, audit enquiries, etc.) to keep a tab on their deliverables. The confidence of meeting the EBITDA and Cash targets slowly drifts, and the actual performance gap at the end of the period also requires its fair share of time.
Measures that cannot be influenced in execution mode inevitably lead to unexpected results
There always exist unexpected results at the end of a period, despite a seemingly endless list of measures that are regularly tracked. This is primarily because delivery teams are not always in control of LAG measures such as EBITDA and Cash. Therefore, it is imperative to focus instead on measures that the team does have the power to influence and monitor in execution mode, otherwise known as LEAD measures.
Measures that allow strategy modification in execution mode are much more effective
Collections, a critical yet highly unpredictable area, stands to benefit immensely from a LEAD indicator to guide teams through the month, much more so than deploying corrective actions after missing target. Upon pushing the team for such an elusive measure, the key insight was gleaned from the month in which the target had been met. In that period, the collection plan had been rolled out along with customer and invoice-level data by the 2nd, and the resulting cash actual achievement was fairly within reach of the estimated targets given. My Controller’s insight on deeper analysis was simple yet effective: what made this month’s target achievable was focusing collections on the top 5 customers by mid-month. Dashboards were modifies to reflect collection performance of specific customers within a certain date as the predictors of the month-end cash position.
- Focus on LEAD measures proves more effective than corrective measures after a missed target
- LEAD measures can be influenced in real time, giving greater control over target achievement than LAG measures
- LEAD measures eliminate the possibility of unexpected results that may arise despite exhaustive tracking of LAG measures
I have even put these LEAD measures and their efficacy to the test in everyday life. In the case of my son’s exam preparations, simply following up with him on the “actual goal”, instead of the preparation work which would directly impact his final scores, and which he believed he had complete control over, would not do, and so we met each other half way. Applying the same concept of LEAD indicators that helped my collections team succeed, we agreed upon “100% completion of each subject portion with one revision in exam holidays per a scheduled time table”. If the daily deviations from his time table went beyond 20%, it would prompt a recast to his schedule. Needless to say, he was delighted by the fact that he could monitor and influence his progress, and that “reporting” back to me acme down to a bare minimum.
Just because a lot of businesses do it, doesn’t make tracking LAG indicators the most efficient
Ironically, LAG indicators, which are outcomes of actions over a period and for the most part merely academic, are what businesses track to monitor performance. However, applying the LEAD measure has proven to work in more instances than one, such as the Network team of a telecom company that had customer satisfaction (C-SAT) as a key metric, who changed their focus to “Network Uptime %” as an actionable metric, leading to higher C-SAT scores. The differences was that Network Uptime % was a metric that was understood and influenced to improve by the entire Network team, whereas C-SAT scores gave them no leverage to work with whatsoever.
Conclusion
It is not an easy process, but identifying a LEAD measure that reasonably predicts the outcome and is within the influence of the team, makes target predictable. This takes the responsibility and accountability back to the operating team, and not the CEO.
This is how I eliminated the need to relentlessly scrutinize my son’s progress, for now he is scrutinizing it himself!
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