Since the industrial revolution companies have been pursuing ways to quantify workforce productivity and the differential value that top performers contribute versus average performers. Back when most jobs were either direct sales or were involved in manufacturing and production of products it was far easier to simply measure the amount of sales a sales person generated or the amount of widgets a manufacturing person assembled. Today, manufacturing and business has become increasingly complex with rapid advances in technology spawning tremendous growth in engineering, I.T., marketing and finance, compliance and other professional and highly technical roles.
Why is it that we can do heart transplants and go to the moon but cannot seem to quantify the productivity of the total workforce and critical job roles?
My opinion is that this is not a challenge of complexity and technology since far more complex challenges have been conquered in the world and software/web technology has made dramatic advances in recent years. I believe the true problem has been a lack of data and a lack of will on the part of HR to attack a complex and challenging problem.
The workforce can be measured, it can be controlled, and it can be managed. Therefore, it can and should be reported as a part of public financial statements or as a supplement to financial statements.
Since workforce productivity for today’s complex job roles has yet to be meaningfully quantified, this challenge requires a new approach and a consistent process. Such a process must measure workforce productivity in aggregate but more importantly, by job role. Such a process must also work across industry, geography, size and complexity.
The place to start is by measuring groups of key job roles in the workforce across all areas of the talent management lifecycle. Each area of the talent management lifecycle then is broken down into a series of advanced metrics, each of which links to productivity, performance, cost, customer satisfaction or other similar key business outcome tied to workforce productivity. Next the differential contribution of the best or top tier versus the average is calculated for the following:
Critical job role/group
High performer versus average performer
High engagement versus average engagement
Additionally, key workforce and HR cost drivers are quantified including:
ROI of career path and internal mobility using Total Cost of Workforce (TCOW)
Cost of turnover
Cost of hiring
Other factors linking key business outcomes (i.e. revenue, customer satisfaction, profits)
While this sounds complex, and it is (why would we in HR think that everything can be done with a single metric or four quadrant chart, is beyond me), there is a workforce ROI calculator that takes key inputs from all talent management lifecycle areas and calculates a differential value for complex job roles.
For example, 10 internally grown high performer programmers with an $80k average annual salary whom are 10% more productive than the average programmer, results in just over $100k annually in differential value creation. Also, reducing the high performer programmer turnover rate by 10% saves $266k annually. Of course there are many other variables at play here but hopefully the concept and value contribution is clear.
While complex, such analysis can be done, it is being done, but real question is, why aren’t you doing it?
For more detail on these and other foundational concepts as well as details on the metrics and calculations involved go to our HCMI site. Also see the groundbreaking white paper entitled Human Capital Financial Statements here.