Our Indian Country Manager, Ramesh Dasary recently published this “5 Best practices for success with workforce analytics” blog post on LinkedIn, and we thought Macromicro fans would be interested to read it.
Do you make decisions about your people with the same rigor and confidence as your decisions about money, customers, and technology or business opportunities?Does your analytics contain stories and insights that readily communicate results and action to your executives? Do you know how you compare to other companies in your industry or region?
At the same point in time, there is an immense change that creates confusion on deciding few best ways in the proceeding and implementing workforce analytics successfully in an organization. In this article, we bring you the best five practices for workforce analytics that in my experience have made organizations successful.
1. Begin with the end in mind.
With his book – The Seven Habits of Highly Effective People – Stephan R. Covey’s fabulous advice of “begin with the end in mind” remains great advice today and is especially relevant for workforce analytics projects. The challenge faced by those implementing or upgrading analytics is that analytics provides for many possible applications: delivering dashboards to executives, measuring the most important HR metrics, creating predictive models of future trends, improving turnover, and many more. Without a clear understanding of what you would like to measure, who will use the information, and what decisions made with the new analytics, the risk becomes failure to satisfy any one stakeholder’s expectations complete. Set clear goals for what the project will achieve, what it will not, and ensure these are clearly communicated.
2. Delivering value at every step.
Ultimately, all analytics projects, workforce analytics included, will be journeys rather than destinations. Organizations cannot expect to take a single leap from no implementation and experience to advanced usage of predictive analytics and planning. Those that have tried to overreach often find themselves either with solutions they can’t use to full effect, or burdened with changing project plans that lead to delay. Conversely, those who have taken a stepwise approach can more clearly articulate and demonstrate the tangible value the project has delivered. This creates many benefits including support for further projects, to more successful training and onboarding of users.
3. Create transparency.
As the adage goes, information wants to be free. Too often we question the sharing of information and seek means to lock it down, to hoard it for ourselves. Certainly, organizations have sensitive data, especially employee data, and must be responsible for limiting access. The challenge is this is used to justify putting information only in executive’s hands, or HR holding too tight to the keys to the workforce data. The value of analytics is to make better, confident, fact-based decisions, but decisions are being made across the entire organization every day. The opportunity is to create a multiplier effect that sees better people decisions made throughout the organization by every people leader. The risk of limiting information sharing is the use of workforce analytics stagnates from limited usage and a lack of alignment or trust that comes from only sharing partial views of information. Challenge what be shared, and work to create a culture that makes information based decisions.
4. Simple is better.
One of my favorite quotes is from Mark Twain, “I didn’t have time to write a short letter, so I wrote a long one instead”. It is elegant captures the notion that simple is harder, and in analytics this is especially true. There is always more information or different ways to show information. The danger with not simplifying is that information overload can be just as dangerous as information under-load as users struggle to understand what is meaningful. Always challenge what information is valuable, versus what information is interesting. What decisions will you make, or what actions will be taken with the information? If you can’t clearly state how the information is used, then challenge the need to include it in your workforce analytics.
5. Don’t ignore the technology.
As a technologist, I know this is easy for me to say, and I also know that many of my colleagues in HR struggle with this one. The key here is not that you have to be an expert, but that you don’t remove yourself from the technology discussion and decisions. There is nothing wrong with relying on experts to provide you with advice, but ultimately you have to ensure the technology will support the goals you are trying to achieve. Ask the curious questions and understand trade-offs that the different solutions may incur.
Workforce analytics suggested reading:
Adopting analytics in HR
Workforce analytics: The three-minute guide
Fact or Hype: Do Predictive Workforce Analytics Actually Work?
The Overlooked Audience for HR Analytics
Macromicro: Creating Transparency in the Workplace
Ramesh Dasary is the Indian Country Manager for Macromicro, a Boston-based cloud-enabled software company that provides visualized workforce analytics for business leaders and data analysts to quickly see and contextually understand their organizational complexity. You can follow Ramesh on Twitter at @RameshDasary or follow Macromicro at @Macromicrollc. If you are interested in learning more about OrgInsight, please click here to learn more or here to watch OrgInsight video demonstration.