Part I: Introduction
This article is the first in a three-part series explaining how the scientific method can be used to increase the effectiveness and profitability of people analytics in corporate environments. Part I offers a rationale for using the scientific method. Part II explains options for its deployment and Part III compares it to alternative people analytics practices.
Scientific Decision-Making in Organizations
Owing to the significant social and health risks associated with the release of a new drug, pharmaceutical companies are legally required to deploy a process – known as a clinical trial – to demonstrate, for example, that the proposed drug is fit for purpose and that it does not result in unmanageable side effects. Clinical trials, in turn, are based on the scientific method to establish causality beyond reasonable doubt (Figure 1). Many of today’s business analytics practices are in fact drawn from the scientific method.
However, the scientific method is not merely confined to manufacturing and R&D functions in business: marketing, procurement and finance functions have also benefited from its use for at least the last 20 years. For example, prior to investing in a campaign, analytical marketers use A/B testing – a technique based on the scientific method – to demonstrate which marketing campaign will deliver the greatest return on investment (Figure 2).
Yet when it comes to people analytics, only a few companies – like Unilever for example – use the scientific method to guide their investments in people programs (see Figure 3).
This is remarkable because many companies that are using the scientific method to improve their marketing, procurement and R&D decision-making choose not to use it when it comes to guiding their people investments; despite the fact they spend more on people than they do on marketing, procurement and R&D combined. Instead, these companies focus on entirely low-level people analytics techniques like HR reporting, visualization and dashboards to deliver their people analytics results.
Why are these companies not using the scientific method? There are at least two possible reasons. Firstly, many lower level people analytics approaches like HR reporting, dashboards, and visualization can be learned at post-conference workshops or on one-week courses. In contrast, the scientific method requires a significantly higher educational investment, typically a postgraduate research qualification. It may be that some HR functions, unlike their marketing and R&D counterparts, are not willing to make this investment.
Secondly, the scientific method is not widely publicized since it is not in the interests of technology companies to do so. This is because the scientific method requires significantly less technology to be effective than lower-level analytic approaches which rely on vast quantities of data and technology upon which to display it (rather than analyse it). Technology companies are therefore unlikely to promote high-level analytics techniques which would reduce their sales revenues. The result is that technology companies have “trained” the market to think about people analytics as a technology-driven discipline.
There is, of course, a place for lower-level analytics like dashboards, visualization and HR reporting in people analytics. In fact, they are essential for statutory reporting and business problem identification. Unlike the scientific method, however, they cannot establish causal links between people processes and desired business outcomes; nor can they be used to identify those people processes which require modification to enable the business to achieve its business objectives.
The result is that companies which focus purely on low-level people analytics are likely to be wasting a significant proportion of their human capital investments. The phrase low-level analytics deliver low-level returns has never been truer and is undoubtedly leading to Gartner’s Trough of Disillusionment in the people analytics industry.
The next article in this series will describe a methodology for implementing the scientific method.