We all make decisions without data sometimes. Oftentimes there’s no other option and time won’t wait. Parents do it every day when it comes to raising their children. Teachers do it when managing their classroom. Doctors do it when there’s an urgent need with no time for a test to verify a diagnosis. And sometimes, business leaders make decisions to break into a new market or invest in solving a hidden problem because the opportunity arises and everything they know inside and out says, “Yes, let’s do this.”
In other cases, people can’t make decisions because they have too much data – or at least not the right data or analytics to generate relevant, actionable insight. This “more is better” way of thinking about data and analytics leads to an everything-but-the-kitchen-sink approach to making decisions. Not sure what to do? Throw more data at the problem and see what sticks.
But as with most projects, throwing more resources – both people and data – at a problem can lead to “analysis paralysis.” In such cases, either you can’t see clearly through the chaos to make a decision, or you end up applying a bunch of arbitrary, unrelated data to a new kind of problem and coming up with muddled view upon which to make a decision or recommendation. The problem is, it’s not necessarily the “best” one. This, of course, defeats the whole purpose of analyzing data and generating insights in the first place. They are supposed to make us smarter – help us see things we couldn’t on our own – so we can make the best possible decision to drive the best possible outcome and do so faster and with less effort.
The best decisions are made when you look at the right data at the right time and analyze it with the right tools.
This is true for business decision-makers – and for everyone else, too. For example, before I start a drive, I always check Waze first. I know my preferred and likely best route. But Waze captures real-time data from people actually on the road, deriving traffic patterns, identifying accidents, and more. So, it can provide a data-driven recommendation that ultimately helps me get to my destination faster, safer, and easier.
Put simply, by using Waze, I become more intelligent and therefore able to realize my objective. Similarly, when your organization uses the right data and analytics tools to support decisioning, your enterprise becomes more intelligent – and thus better able to achieve its goals such as executing strategy, driving revenue, managing costs, or mitigating human capital and business risks.
The question is, how do you avoid the pitfalls of kitchen-sink analytics and analysis paralysis?
SAP understands this common challenge and has created resources like “100 Critical People Analytics Questions,” which is geared for human resource professionals and talent managers. These questions are designed to help decision-makers think critically about the talent management issues they face and what data and insights will have the greatest impact on their organization.
Rather than looking at the “kitchen sink,” it is recommended that you select the top 10 to 15 questions that most impact your organization’s ability to execute your strategy, drive revenue, manage costs, or mitigate human capital and business risks. Selecting a subset is also important for the next steps – setting targets and assigning staff resources to implement interventions and monitor progress, both of which are more feasible with a smaller number of metrics. The document also provides guidance on selecting key performance indicators (KPIs) that can demonstrate progress toward addressing your specific questions.
For example, if your business strategy is to increase market share, focus on questions relating to talent drivers that impact the execution of that strategy and the metrics that HR should monitor to demonstrate progress toward strategic goals, such as:
Average manager tenure
Employee retention index
Managerial quality index
Staffing rate – expatriates
Training hours per full-time employee
Here are five recommendations for how to select and manage a set of KPIs.
Focus on a small core set of KPIs.
When in doubt, leave it out. Select only as many KPIs as you can actively manage. Resist the temptation to include everything you can measure as a KPI. Use three key criteria: a clear link to strategy, a willingness to set targets against the measure, and a willingness to commit resources to managing progress.
Get management buy-in and continuous support.
The saying “what isn’t measured, isn’t managed, and what isn’t managed, isn’t done” applies here – active support from executives helps ensure that progress is tracked. Several organizations involve their CEO or head of business unit in KPI selection workshops, which helps with the challenge of gaining executive support. Firms also routinely report performance against KPIs to their boards or executive committees.
Help ensure data quality.
Nothing makes managing KPIs more difficult than suspect data, so you should spot-check the data needed to populate your KPIs. Conduct a structured data verification process to help ensure definition consistency and data validity.
Communicate performance actively and often.
Keep KPIs top of mind. Reports, social media, e-mails, conference calls, and manager question-and-answer sessions all help reinforce the importance of the business objective being measured by a KPI. You should set targets and use benchmarks wisely.
Revisit KPIs periodically.
As your organization’s strategy changes, so should your KPIs. Your organization should actively pressure test your KPIs at least once a year. Armed with the right data-driven metrics and insights, your organization can better execute your strategy, drive revenue, manage costs, and mitigate human capital and business risks.
Want to learn more about the power of data-driven decisioning for human capital management – and how you can start taking advantage of SAP SuccessFactors Workforce Analytics quickly?