Fine Tuning Your Workforce with Analytics: Page 2
6) Analytics is not an IT systems implementation project. It uses a framework based in established social science and business management practices to understand what a company is asking of its workforce, how it needs to organize that work, and how to find and allocate workers who are qualified, interested and willing to do that work. Once those workers are in place, the company must know what is needed to support workers’ engagement and commitment to the goals of the company: the right leadership culture, and appropriate development and training, performance metrics, tools, working conditions and rewards.
Only at the point that this complex of interrelationships is well understood do systems come into play to support the fact-based transformation of how the company operates. At this point the company can start to build the data warehouses, decision support tools, and distribution systems that are required to manage their workforce more effectively.
All: What are some of the biggest challenges associated with workforce analytics?
Hoffmann: There are four important challenges that “Calculating Success” is devoted to overcoming:
1) There is still a view that competitive advantage is found in market differentiation, pricing, the use of technology and rapid adaptation to the changing competitive marketplace. The workforce is too often viewed as a cost or burden common to all competitors rather than a source of competitive advantage.
2) At the same time, there is a view that the use of data in managing human resources is inhumane -- that using mathematical models to manage people indicates that managers see people merely as widgets in their inventory.
3) Many managers have been rewarded for their intuition and believe they “know their people.” Even though this intuitive approach can miss critical dimensions of worker performance, breaking that pattern of decision-making is difficult. It also relies too much on a small set of very gifted executives. Without a systematic and reproducible approach to competitive challenges, it can inhibit the passage of knowledge to successors.
Most executives also feel the pressure to move quickly and worry about “analysis paralysis” and “boiling the ocean” with unmanageable reams of data. They often avoid bringing in “academics” whom they feel will not quickly understand the complexity of their business and who often speak in a language they don’t understand.
4) There are many challenges associated with getting access to information across systems throughout the organization, and the perception of these challenges often prevents the inception of workforce analytics projects. The technical complexity of getting access to data from a variety of different administrative systems is a reality, but the territorial aspects of overcoming organizational boundaries is often more difficult.
Determining who owns the systems, whose budget pays for the data integration, and how priorities are set often requires great diplomatic skill. Building a foundation for finance, operations, marketing and sales to share data cooperatively requires a compelling business case with demonstrable benefits, a budget and recognized and controllable risks.