Workforce Management Goals And Data Insights: Applying Embedded Analytics To HR

Kim Lessley

Part 3 in the “Embedded Analytics” series that explores the many ways that companies across industries are using analytics to support innovation.

Across industries and geographies, HR organizations today face no shortage of challenges. In this blog, I’ll cover three of these challenges in particular, and then look at how embedded analytics can help address them.

1. Blended workforce management

To stay competitive and accommodate employee demand for flexibility, today’s organizations are finding new ways to take advantage of the best talent available. As a result, today’s workforce is made up of both full- and part-time employees, sometimes in job-share arrangements, working in collaboration with “gig economy” contributors (contingent labor, freelancers, contractors, and consultants). Some work onsite, others remotely. Teams are often dispersed globally with greater diversity by age, gender, ethnicity, life experience, and more.

But how can you manage all these populations? How do you ensure that all workers are woven into your culture and included in your processes? How do you make sure they are getting the job done?

2. Diversity and inclusion

Studies show that workplace diversity is good for business performance – but when career tracks typecast potential new employees, finding qualified people can be an obstacle. In response, talent managers are thinking outside the box. In some areas, for example, recruiting is moving away from a focus on pre-defined qualifications to a broader search for capabilities that – with the right training – could be harnessed to meet the needs of the position and the company.

But how do you move forward? How do you monitor and measure team diversity? How can you ensure that your recruiting and talent management initiatives deliver on diversity goals – and if not, how can you correct course?

3. Employee experience

In their personal lives, most workers enjoy the simple “tap, tap, buy” experience of slick mobile apps designed with the customer experience in mind. Now they expect the same at work. And beyond their expectations for the tools, today’s workers often prioritize a different set of values – such as purpose over pay, belonging over career development, or recognition over job titles.

How can you deliver experiences that keep employees engaged? How do you instill a sense of purpose? How can you make sure that your organization is the kind that attracts and retains employees by responding to these demands?

A new kind of analytics

Analytics can help you move forward on all these fronts. But traditional analytics fall short when HR people have to rely on specialists to generate the reports they need. Often, workforce data resides in warehouses disconnected from operational systems. Today’s HR teams need insight faster.

This is where embedded analytics can help. With embedded analytics, live and historical data live together on the same system – supporting a single source of truth. Insight is built directly into your workforce applications and processes, instantly accessible to users for self-service reporting in their daily activities. Embedded analytics is a first step in your journey to contextualize insights across the enterprise by leveraging business intelligence (BI), planning, and augmented analytics in an all-in-one solution.

Embedded workforce management

Embedded analytics can help your HR team better manage a blended workforce. For any given project, you can look at specific key performance indicators (KPIs) for, say, work completion – and then break down the results according to worker categories such as full-time, part-time, and contingent. Where discrepancies between groups are revealed, you can explore the root cause.

Is the problem isolated to a particular region or group? Is it a lack of training for certain worker categories? Do process gaps lead to miscommunications? With proper analytics built into processes, you can identify factors that put projects at risk. Then you can take action accordingly, without waiting for a separate reporting entity.

Embedded diversity and inclusion

What about diversity and inclusion? With embedded analytics, your HR team can monitor diversity gaps and develop a holistic view of workforce composition. You can identify hiring gaps by gender, ethnicity, age, and other metrics. You can also monitor salaries, bonuses, and performance data to ensure equitable compensation.

By bringing to bear predictive technology and machine learning, you can go further. By analyzing turnover rates, for example, you can break down the data with enough granularity to predict the risk of employee churn. Or you could use machine learning algorithms to run through job advertisements and uncover language of unconscious bias – helping your team compose ads more likely to attract candidates who don’t fit the stereotype.

Embedded employee experiences

If the employee experience is the sum total of all the interactions the employee has with your organization, then it’s important to pay close attention to those interactions. Embedded analytics can help your HR team track every worker touch point.

You can measure which workers opt out of certain processes, for example, and determine whether your systems stand in the way. You can track engagement metrics to predict the success of certain initiatives. You can also use analytics to proactively improve the employee experience itself – say, by pushing out recommendations based on predictive analysis. Which new training course or workshop would benefit a particular employee? Which mentor can you pair with another employee based on identified career goals? This approach can drive better employee experiences – and ultimately, improve employee engagement and organizational performance.

Getting started

Starting small is a smart approach with embedded analytics. Rather than setting out to reduce attrition company-wide, my recommendation is to focus on a particular problem such as persistently high turnover rates in a particular region. What stage of the employee lifecycle correlates with the timing of employee departures? What compensation plans or training are associated with retention? With insights gained from initial projects, you can expand to the next use case, fine-tuning your approach and gradually applying embedded analytics on a broader scale.

For more information, download the March 2019 Forrester Consulting opportunity snapshot “Optimize Business Intelligence Efforts With Embedded, Application-Driven Analytics” to examine the challenges, best practices, and recommended actions to turn your business into an intelligent, competitive force.

Gain real-time insights into your data beyond human bias with the help of SAP Analytics Cloud! Join our webinar series starting on June 11th and learn how to turn data into a strategic asset by utilizing AI and predictive analytics.


Kim Lessley

About Kim Lessley

Kim Lessley is Director of Solution Management for Cloud Security at SAP SuccessFactors.