Welcome to the second module of People Analytics. It is devoted to employee performance. Employee performance is the most significant metric that exists in human resources management. In a great number of organizations, a lot of HR statistical data deals with human resources department's activities. While it is indeed important to keep track of many things, from average time to hire to employee satisfaction, the key thing every CO is worried about is the organization's performance. By managing performance of individuals and teams, one can manage performance of an organization. And you cannot manage what you cannot measure. Therefore, for HR to play a more important role in the organization, it is crucially important to identify talent management related factors that impact performance, and use other data to find out what HR management instruments can further improve performance. That is the reason we start this class with a module devoted to proper identification of top performance in organizations. Identifying factors that contribute to performance is the first step in using data to improve other HR processes, as it allows us to calculate return on investment in HR management by connecting business results and HR processes. For example, Time Warner Cable uses connection to performance to evaluate the business value of talent acquisition. Talent acquisition data are evaluated against key employee performance metrics, such as number of sales or percentage of issues resolved in one call. For example, Time Warner's talent analytics showed an average customer service agent who scores in the top quartile on the pre-hire assessment of sales focus [INAUDIBLE] as much as 70% more sales revenue than the average agent who scores in the bottom quartile. High scores on customer focus also prevent 90% more costly technician visits to customers by resolving more issues over the phone. This leads to lower costs, higher margins, and better customer experience. Although performance evaluation may sound simple, it is not. So, what exactly do we have to measure? Measurement of employee productivity and effectiveness can be traced back to the days of scientific management of the late 19th century, when the wide spread of industrial manufacturing raised the question of getting better outcomes from employees working in similar conditions yet producing different results. Quantitative analysis and its use in decision making were first developed during the 1940s. Common HR metrics in existence today were first developed during the 1970s. In the 1990s, key performance indicators were united in balanced scorecards. This is essentially a dashboard of financial and non-financial measures of a company's performance. Its key is to connect strategic and operational goals of an organization. The next stage is to connect operational goals to individual performance. So step one in performance measurement is to define what a proper performance metric for every individual means. When doing that, one needs to remember several things. First, measuring performance also directs it. Performance goals will create incentives to change behaviors, even if they are not directly connected to compensation. Second, you need to actually measure something aligned with business goals. One of the keys to setting up proper performance metrics is to think how each and every individual in his own function can best contribute to achieving the organization's overall goals. Moreover, if your KPI is not appropriate, the resulting behaviors may be counter-productive. For example, using the same goal of providing superior customer service, the first KPI that often comes to mind is number of customer complaints received. One may think you may feel that the fewer complaints you receive, the higher the customer service you're offering. That is not necessarily true. You may be getting fewer complaints because you have fewer customers or because customers are not able to access your support services. In another example, an international industrial company has set a KPI for its supply function leader to cut costs as much as possible. Although the intention to keep production as lean as possible is reasonable, a KPI set this way creates incentives to make sub-optimal managerial decisions. For example, if a manager needs to make a decision whether to purchase materials or equipment either in time but at a higher price, or with a delay that will eventually cost the company more but will make the procurement technically cheaper, the manager is likely to make the sub-optimal decision that is in the end not in the interests of his company.
