Wednesday 12 April 2023

mmmmmm, More Meaningful Management Metrics


For about a week, I've enjoyed following and participating in an expansive discussion thread on LinkeDin about the value of measurement and metrics for management, debating various issues that can occur both in theory and in practice.


One straw-man argument is that 'managing by the numbers' can imply a myopic focus on commonplace business metrics such as stock price or annual profit, both of which can be manipulated to some extent by managers even at the expense of long term resilience and commercial success, let alone other business objectives. Despite Taylor's outmoded 'scientific management' experiments having been debunked a century ago, some LinkeDinners in the thread evidently still believe that science (in the form of numeric data) and management are poles apart. 

I beg to differ. That's so last century!

Management is complex, dynamic and nuanced, hence I accept that simplistic or crude metrics can't possibly address the entire practice. For example, speed is obviously a key metric for a racing car: however, going fast is just one part of racing, even on the drag strip. Staying on-track with both vehicle and driver holding together for the duration of a meet are also important for the team manager, the whole team in fact. An exploding drag car might conceivably project sufficient material across the line to qualify in record time, but there would be nothing left to compete in the final! 

If workers are rewarded for their personal performance as crudely measured by, say, the number of widgets they produce on a shift, there is implicit pressure to churn out the widgets regardless of their quality, the costs of manufacture or other relevant factors such as shift length, breaks and teamworking. With inappropriate metrics, quickly producing 100 widgets, 20 of which are quality control rejects, may be a more attractive option than carefully producing a lower number of perfect widgets. 

That is an example of 'gaming the system', also known as 'surrogation' or 'Goodhart's law' where a metric itself becomes the prime focus of attention and effort, rather than whatever is being measured. The Oscars are a classic example: being an Oscar winner has become a central and valuable goal in its own right with tremendous publicity and hence commercial implications, even for nominees. Producing an Oscar-worthy film is not quite the same as producing a good film: goodness is potentially skewed towards whatever the Oscars supposedly reward this year. 

Rather than elaborate further on the issues (see the LinkeDin post and comments instead), I'm writing here in support of measurement and metrics for management - specifically the incorporation of relevant, meaningful metrics to guide management decision-making and drive improvements in the business.

A set of high-level 'enterprise metrics' concerning various strategic aspects of the business (financial performance, customer satisfaction, employee engagement, risk, innovation, sustainability, resilience etc.), particularly those relating to the organisation's business objectives, can provide a rounded and predictive yet succinct perspective for senior management without over-emphasising or ignoring individual elements. The approach is fractal in that it also applies within each unit or domain of expertise, providing relevant although more narrowly-scoped and increasingly tactical 'business unit' or 'departmental' metrics for middle and junior managers and so on all the way down to operational team metrics and individual performance metrics. 

Thinking of and designing the organisation's entire suite of metrics in these terms can ensure the information provided satisfies the information requirements, forming one coherent measurement system. Explicitly linking metrics to objectives at each level is key, not least because it forces management to elaborate on those objectives in measurable terms. 

As well as reporting and using the information, reviewing/evaluating and fine-tuning the metrics should be an integral part of management's routine, driving continuous improvement. For example, metrics may need to be adjusted to remain aligned with evolving business goals and pressures, identifying and responding to emerging trends and changing information needs, reflecting and promoting a gradual maturity. As I see it, the measurement system is a dynamic, living construct, an essential component of information flows, just as important as an animal's senses. 

A corporate policy of 'no surprises', coupled with a genuine committment to address issues raised at all levels, brings both the metrics and the management information flows to life - and both parts are valuable. The raw metrics data make more sense if graphed and statistically analysed, more still if explained with relevant contextual information leading to knowledge and actionable insight. So, in a sense, the numbers themselves don't matter except in as much as they support and drive decision-making.  [I'll sidestep the distinction between objective and subjective metrics for now. Bottom line: they are complementary, not alternatives.]

While metrics can suffer issues such as gaming and surrogation, a well-designed and comprehensive measurement system can be immensely valuable - invaluable in fact. By aligning metrics with business objectives, promoting a culture of continuous improvement, and ensuring that all levels of the organization are actively engaged in the provision and use of information, management can effectively leverage metrics to support and drive decisions and activities inexorably towards the achievement of business objectives. 

Result!

Finally, I will briefly mention assurance. It's all very well if suitable metrics and other valuable forms of management information are flowing sweetly throughout the enterprise but can they be trusted? Do they, and the associated data gathering, analysis and reporting activities, have sufficient integrity (accuracy, timeliness, relevance, credibility ...)? Is that at least demonstrable and testable, if  not strictly provable by some independent authority? Assurance is a distinct but related and parallel consideration in the design of a measurement system, with several information risks and mitigating controls ... that I will leave for another day.

Meanwhile, do get in touch if this piece has sparked your imagination, especially if you are inspired maybe to give it a go in your business. I enjoy leading/supporting clients through the process of clarifying their measurement objectives and selecting suitable metrics to plug in to their bespoke measurement systems. How about we set out by talking through your situation and options? 


PS  'Meaningfulness' is just one of nine PRAGMATIC metametrics criteria. Can you spot the others in this piece? 

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