ATC 10 Feb 2015
You can read part one of this article, here.
In my article last week, I discussed the top design principles I believe you need if you are to successfully shift to a data-driven decision-making model in Talent Management. Shifting to a data-driven model brings your function into alignment with almost every business function, like supply chain, finance and CRM. All of them long ago shifted to metric driven decision-making because it allows you to demonstrate your business impacts.
In this weeks post I outline the the administrative actions that need to follow these design principles, to get the most out of your metrics.
Administrative actions to follow
There are also principles relating to the administration of metrics. They include:
- Work with the CFO – work directly with the CFO’s office to ensure that whatever you do in the metric area is credible with the undisputed “king of metrics”.
- Prioritize your metrics – prioritize your highest impact metrics and focus on measuring and improving the 20% of your metrics that are truly strategic.
- Limit the number of metrics that you report – you only need to report to executives metrics that cover each of your Talent Management strategic goals. In most cases, that is 10 or fewer strategic metrics.
- Don’t report cost or transactional metrics – focus on strategic business impact metrics and severely limit your reporting of transactional, tactical, efficiency and program cost metrics to executives. Never report costs without also reporting the return or value added from the budget money spent (together they make up ROI).
- Perfect data isn’t the goal – realize that all metrics and data sets have flaws, so the goal is not perfection but rather simply to have data that is considered credible by managers, executives and the CFO.
- Focus on internal comparisons – year-to-year and internal metric comparisons are superior for decision-making. External benchmarks are weak, because other firms use different formulas and data sets.
- Tie metrics with rewards – adding performance rewards to metrics drives action even faster than metrics alone.
- Widely distribute ranked metrics – widely distributing metrics that rank performance by the individual manager will also get everyone’s attention quickly. These metric reports have the added benefit of revealing to everyone the managers that can provide the best advice on improving performance.
- Build an analytics team with business experience – a high level of business acumen within the team helps to ensure that everyone in the team understands that the goal is to get managers to use data for decision-making and to ultimately improve their business results. Team members should also study the advanced metrics found in baseball and at firms like Google or Intuit.
Whether you work at Google in the Silicon Valley, a multinational firm in Sydney or a small bank in Adelaide, I have found that the metric design principles that I have provided here work equally well. Metrics designed with these principles will allow you to show and qualify your direct business impacts, and that will lead to better funding and executive support for your new talent management initiatives. And finally, the addition of predictive analytics will allow for the early identification of upcoming talent problems, so that you can minimize their negative impacts. Overall, I would suggest that it’s time for everyone to stop merely calling themselves “a business partner” and instead to finally become metric driven, like the rest of the business. In Talent Management, we need to forever ban the all too common phrases “I think”, “I believe” and “I feel” and replace these phrases each time with… “the data shows”.