An effective change management and communication plan is critical to the success of building a data-driven culture
Most companies have identified that employee engagement is key to organizations’ success. But, can we measure the impact of engagement on a company’s bottom line? A few years back this would be in the wish list of most CEOs or CHROs but today, the day is not far where we can accurately measure a clear ROI of investment not only in employee engagement but for Learning, Compensation, Benefits and Talent Acquisition. A 2014 HR Survey of CHROs predicts 66 percent of the organizations significantly increasing investments in Workforce Analytics. Another 2004 HR Technology Survey predicts that the biggest growth area of HR technologies is in the area of workforce Analytics from 14 percent to 46 percent in the next 3 years.
While there is no doubt that building an HR analytical function and capability is high priority for CHROs, how do we get started? We start with asking ourselves a few fundamental questions:
Develop a clear objective and impact assessment
The first priority for HR Analytics is having a clear-end objective and impact. We started with stakeholder interviews with global HR Leadership that helped define and refine current strategic HR and business priorities and find a link to how data and insights would enable making effective decisions. As an example, one of the strategic priorities for us is to improve our customer centricity. A very powerful way of leveraging people insights in the customer centricity transformation is to find the co-relation between customer experience scores, engagement scores and voluntary attrition of customer facing role.
Once there is a clear set of objectives to focus on where HR insights would help, it’s important to prioritize the objectives in two ways:
- Prioritize objectives by the level of impact it would create and ease of deployment. The ones with the highest impact and higher ease of deployment are prioritized.
- Prioritize objectives based on HR Analytics maturity model (simple reporting, complex reporting, prescriptive Analytics to predictive Analytics)
While the scope of HR Analytics may be huge (reporting, complex reporting, benchmarking Analytics, social Analytics and predictive Analytics), it’s important to identify the ‘Quick Wins’ based on impact versus ease of deployment.
Create a high mindshare and organizational alignment
Getting stakeholder alignment and mindshare early on is critical to the success of building the HR Analytics function. Many a times it’s common to find that Analytics CoEs located in India are disconnected from the actual customers and stakeholders. The link and line of sight between creators and consumer of HR metrics and insights are broken. Engagement with HR leadership and stakeholders is critical for alignment, mindshare and driving a data-driven culture.
Develop the right team
In most organizations, current HR teams do not have the skills to build and execute HR Analytics as the skills needed are beyond the traditional HR skills. Secondly, HR leaders may not have the
understanding and knowledge to build a team that consists of diverse skills like Statistical modeling, Data visualization, Project Management, Database and IT Architecture skills. In India, there are a handful of organizations that have evolved from complex reporting to prescriptive Analytics, and hence the talent pool is limited. Given the limited pool of talent in HR Analytics, it is prudent to hire non-HR Analytics resources and train them on HR than hiring HR Generalists and training them on Analytics.
Focus on good quality and quantity of data to analyze
Building a good analysis is akin to cooking a great meal. If the ingredients are of good quality, using the culinary skills one can be assured of a great meal. If we use poor quality ingredients, we would get poor quality of meal. Good ingredients to prepare a meal are similar to good quality of data. In a recent Economist Intelligence Unit survey of 530 senior executives, data collection is cited as “very important/essential” by 76 percent of executives from top-performing companies.
While it is important to focus on data quality, it is equally important set expectation with stake holders on the assumptions and approximations related to data accuracy before undertaking any analysis. Sharing initial findings with selected stakeholders help in understanding if there are large variances because of data gaps.
Evaluate building it in house or buying HR Analytics services
The decision to build HR Analytics or buy HR Analytics services lies with a host of factors like stage of organization’s preparedness, timeframe to deploy Analytics, IT capability and infrastructure, budget and culture. At Lenovo, we evaluated carefully and weighed options against the above parameters, invited consulting/technology companies for proposal offerings and collaborated with peer companies who have implemented HR Analytics. Based on the above parameters, we decided to develop in-house capability and leveraged Analytics expertise that already existed in some of the other internal functions like the marketing and strategy teams.
Build a data-driven culture to make decisions
Many a times, change management related to building a successful Analytics function is underestimated and an effective change management and communication plan is critical to the success of building a data-driven culture. Data and insights should be at the heart of every decision making process. At Lenovo, we integrated HR Metrics and insights from HR Analytics with key organizational programs like Talent Review, Performance Management, Rewards and Recognition and HR communication. Further, we built HR Dashboards for senior HR leadership team to identify organizational priorities to focus upon and follow that up by building trends over a period of time.
Measure ROI of HR Analytics investment
The real power of HR Analytics and its ROI can be measured on the basis of the business outcomes it delivers. As an example, with the help of analyzing and linking the data of customer-facing roles related to employee engagement, employee retention & attrition, sales productivity and customer satisfaction, organizations can draw insights and implement actions that would help in generating higher revenues. For example, a large global retailer has precisely identified the value of a 0.1 percent increase in employee engagement among employees at a particular store has resulted in more than $100,000 in the store’s annual operating income.
Finally, Analytics is a journey and not a destination!
Analytics is a journey and not a destination. In that journey, there are successful milestones and pitfalls, opportunities to find alternative paths and learning from the experience. It’s a journey where one path can lead to a newer and better path that has not been discovered before. Just like in any journey, one may get lost, in Analytics it is important to keep the end goal and business outcomes in mind and prioritize the width and depth of Analytics. Finally, Analytics should be used as a decision support tool and not replace human decisions.