Self-service headcount analytics using Microsoft BI: succession planning

Jason Drucker

Jason Drucker

Many of today’s executives are concerned about the balance of resources across their company. Ideally, they would like a proper blend of experienced veterans and cost-efficient junior resources to fill out the roster, but currently have no simple insight into employee tenure and experience. As executives begin to think about this relatively unchartered territory of talent analytics, many questions are being asked, such as:

  • Which positions in my company have the most experience?
  • Are our resources improving over time?
  • What are the most effective training plans?
  • Are we prepared to quickly and efficiently replace an employee with minimal setbacks?

Implementing a Succession Planning solution can empower a company to answer all of these questions with quick, easy-to-use self-service BI dashboards. The succession planning story below was built using the Microsoft BI solution stack and can be implemented with any company that captures performance and training information.

The scenario

Sally is the Director of Human Resources at a company with over 10,000 employees. She has been tasked with investigating which departments are properly managing and retaining their talent, as well as exploring different avenues to improve department training programs. Sally starts by opening her Tenure Analysis Power View dashboard in SharePoint 2013 and notices that the engineers have the most tenure. She clicks on the engineer title, and the Power View dashboard reacts to the click, showing engineer employee details. There are 5 engineers in the region, and the team has an average of almost 10 years’ experience.

Tenure analysis succession planning

Sally wants to see if this high tenure is leading to top-notch performance for the engineering team. She opens her next Power View, which analyzes performance over time for each engineer. The time series option in Power View allows a user to easily digest a large amount of information quickly. In this time series, Sally is viewing the amount of tenure on the job (x-axis) vs. the employee’s quarterly performance rating (y-axis), which is data that has been integrated directly with the Headcount Analytics solution. Each bubble is a different employee, and the bubble size shows the running total of training dollars spent.

Performanc Ratings Analysis

By clicking on an employee, Sally is able to see an employee’s changes over time. Looking at the two most tenured engineers, Sally notices a difference in performance. Stefan (in orange) has continued to use his training budget, as evidenced by the progressive increase of his bubble size. This continued training has produced the model employee, as his recent performance ratings have been nearly perfect. Meanwhile, Brandy (in blue) stopped utilizing the training program, as shown by her constant bubble size after her first few years with the company. Brandy’s skills have lagged behind the curve as her trainings ceased, and her performance rating has dropped significantly (see the graphs below).

performance rating time series analysis 1performance rating time series analysis 2

Sally is concerned about Brandy’s performance drop, and she wonders if the company is prepared to handle succeeding Brandy if needed. She looks at the details for the next tenured employee, Thea (in purple). Thea has progressed excellently over the past couple years, mirroring Stefan’s career track. Thea appears to be a strong candidate to succeed Brandy if necessary.

performance rating time series analysis 3

Finally, Sally looks at the only junior-level engineer, Beverley (in red). Beverley is off to a rocky start with the company. She isn’t utilizing her training budget and isn’t progressing along the desired growth curve. Sally decides to work with the engineering supervisor to consider switching Beverley’s direct manager to the top-performing engineer, Stefan, for better career guidance. Sally and the managers will monitor the situation closely, and if Beverley’s performance does not improve, they will consider an employee release and replacement with a more suitable junior-level hire.

performance rating time series analysis 4

Now that Sally has looked at individual performances, she would like to evaluate the engineers’ training utilization holistically. She opens her Yearly Training Budget Analysis Power View dashboard and immediately sees a downward trend in training budget usage since 2006. Additionally, the dashboard shows three straight years of declined overall performance. Sally decides to work with the engineering manager to increase training budget utilization across the entire department, which should provide a bump in the overall department performance rating. Since Sally’s earlier analysis showed that Stefan was using his training successfully, she asks Stefan to coordinate the department-wide training, which will help ensure the dollars are spent wisely.

yearly training budget anaylsis

Preparation paves the way to success

Gaining a better understanding of the employee landscape will lead to improved resource planning, timely and appropriate hiring strategies, balanced and effective training budgets, and a clearly defined succession plan. With a well-built headcount analytics solution a company can make great strides in empowering its managers to make sound decisions and continually drive the business towards success.

About slalomjasondrucker
Jason is a Solution Principal focusing in Information Management & Analytics dedicated to providing the ultimate customer service through his hard work, critical thinking, collaboration, and communication skills. He is an expert in end-to-end business intelligence solution architecture, ETL design and development, end user reporting and dashboard delivery, data integration, data modeling, business analysis and project management.

3 Responses to Self-service headcount analytics using Microsoft BI: succession planning

  1. Pingback: Self-service headcount analytics using Microsoft BI: health benefits analysis | The Slalom Blog

  2. Pingback: Self-service headcount analytics using Microsoft BI: payroll analysis | The Slalom Blog

  3. Pingback: Self-service headcount analytics using Microsoft BI: salary analysis | The Slalom Blog

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