5 Ways Six Sigma assures Employee Centric Decision Making in HR Analytics

Six Sigma, HR

As “data-driven decision making” becomes a buzzword, a Deloitte study claimed that over 70% of executives are proactively integrating data into their everyday decision-making. Advancements in analytics are the reason for this paradigm shift.

The Deloitte report also revealed that 84% of business owners and HR executives believe people analytics is integral for organizational success. For instance, in the HR segment, analytics can unearth crucial information about people and process efficiency.

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Firms need to comprehend how HR analytics can deliver desired outcomes. Firms must maintain the long-term feasibility of analytics models. This is precisely where the Six Sigma methodology comes into prominence. Borrowed from the product management playbook, Six Sigma in HR analytics significantly improves data efficacy to reach the decision-making goals.

At its core, Six Sigma aims to cut down the possibility of errors in every production cycle, minimizing the risk of a defect to near zero.  As a result,   Six Sigma places the same benchmark of accuracy and quality of services as expected from a physical product to HR analytics. .. Given the depth of analytics, Six Sigma can break down people analytics into its central components, making results as accurate as possible. A perfect Six Sigma score in HR analytics would mean that 99.7% of all data points are within the ideal statistical range.

But even if firms don’t hit that perfect score, Six Sigma in HR analytics can assist in navigating the complexities of people data and aligning statistical models with real-world business outcomes.

Any Six Sigma project in HR will involve the DMAIC framework – Define, Measure, Analyze, Improve, and Control. In the context of HR analytics, this breaks down into the following steps:

  1. Measure the data across all component functions 

Firms need to have time to gather data for each parameter, either from existing sources or by implementing new ones. If an organization doesn’t have its own people analytics team yet, analytics tools can be extremely useful in this phase.

Firms can collect previously unknown information, create some employee sample sets, and run statistical models to arrive at the Six Sigma score. The score will be anywhere between one and six – the higher, the better.

  1. Define a unique pain point 

What do firms aim to achieve from this Six Sigma initiative? The methodology inspired by project management must have a specific challenge at its roots. Once the pain point is clear, one can dive deeper to create a breakdown of component functions towards its resolution. For instance, time to hire may be affected by the level of automation in the recruitment process, in addition to the number of applicants in the talent pool.

Finally, this will lead to the “ideal scenario” – for instance, a two-week average time-to-hire instead of 1.5 months.

  1. Improve the pattern

To fine-tune influential dataset(s) for better outcomes, HR needs to adopt new technology, rewiring e processes, or enhance employee/candidate experience. This is encapsulated in a “Design of Experiment (DOE)” initiative. DOE converts the theoretical correlation between cause and effect into an implementable experiment, deployed in a controlled environment.

  1. Analyze the outcomes 

Usually, HR analytics implementations are limited just to step two. Organizations measure key impact areas but fail to contextualize this information for genuine action. This is why Six Sigma makes a big difference in HR analytics. Firms can evaluate the data collected and the resulting score to conduct a root cause analysis.

  1. Control the long-term feasibility of the model 

The impact of HR analytics project needs to be sustained in the long term. Continuous reviews, randomized data collection to check if the results still hold, and a renewed application of Six Sigma in HR are some of the measures firms can take.

In many ways, control is the most critical step for using Six Sigma in the HR context. It will reveal the need for new algorithms, opportunities to gather fresh data and “control quality” for the original problem area.

A company’s people assets are at the center of any significant transformation. That’s why it is critical to perform a thorough data analysis before implementing a change. Six Sigma can help leverage critical people data, test the most effective hypotheses, and maintain experience quality in the long run.

With the workforce becoming a significant differentiator for business success, deploying proven and scientific models such as Six Sigma will help to ensure HR analytics success.

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