This blog post is a repost of a PI Worldwide newsletter article that I felt should be shared.
Today’s leadership teams recognize the value of data to solve business challenges and gain a competitive advantage. However, creating the necessary support and sponsorship can be an obstacle to establishing a data-driven culture. As more business leaders look to secure funding for their workforce analytics initiatives, success hinges on their ability to make an effective business case. A May 2014 MIT Sloan Management research study1 reports that investments in analytics have steadily increased since 2009 by an annual average growth rate of 8.5%. Further industry research suggests that organizations making these investments are two times more likely to improve their recruiting efforts and leadership pipelines, and are three times more likely to realize cost reductions and efficiency gains2.
Here are four guidelines to follow when building a business case for talent analytics3:
Define the business issue and determine your key stakeholders. In addition to understanding (and prioritizing) specific problem(s) that need to be solved, you must determine the individuals who will be impacted and involved in the process. Ask questions like: Who owns the issue we need to solve? Who would help champion this program? Who might challenge this program? Start by speaking with internal business leaders, line managers and other executives as you also conduct industry and market research.
Build a compelling solution. Detail the key components of your chosen solution and how it will be implemented. Consider dependencies like time, people and other projects. Key questions to pose include: Where will the solution be used? How will we roll out a multi-phase process? Should we combine the solution with another related initiative?
Quantify solution costs. Detail the hard and opportunity cost drivers of the solution—from the people expenses (e.g. headcount, training, hiring) to process costs (e.g. assessment costs, technology, overhead, etc.). Partner with key stakeholders to guide and validate cost assumptions.
Determine key metrics and define what success looks like. To make a concept meaningful, you need to make it measurable. Determine how you will quantify the benefits of the program/solution in terms of bottom line impact or other drivers that will resonate with your key audiences.
1 Kiron, Kirk Prentice, Boucher Ferguson. “The Analytics Mandate,” MIT Sloan Management Review. May 2014
2 Bersin by Deloitte. WhatWorks Brief. September 2013
3 Bersin by Deloitte. 2014
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