HomePeople AnalyticsPlanning a people analytics revolution? Use an incremental change method instead

Planning a people analytics revolution? Use an incremental change method instead

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Bradford Williams, Head of HR Technology & People Analytics at Northwestern Mutual, draws on ‘The Innovator’s Dilemma’ to offer an incremental change model for people analytics that balances innovation with stability and best delivers enhanced performance and productivity.

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Bradford Williams headshot for article on an incremental approach to people analytics

The world around us is changing. As cliché as that sounds it’s no doubt true. In fact, it’s almost always an accurate statement to make. However, over the last several decades at least, one of the constants has been an increased focus and importance placed on data and analytics. You can argue People Analytics was behind the curve, but we’re here.

Depending on your organization and industry perhaps you’ve been there for a while. This isn’t going away. Organizations will continue to place more emphasis on people analytics to enhance employee performance, productivity, and overall organizational success, among other things. As an illustration, just take a look at Gartner’s 2023 Future of Work Trends and find one trend where people analytics wouldn’t add tremendous value.

Staying up to date with current trends and metrics in people analytics is crucial, but it’s equally important to maintain consistent threads and views so that the audience doesn’t have to constantly adjust to new ways of looking at data. Striking this balance is not only a challenge but also an essential element for achieving long-term success.

Embracing incremental changes: The path forward

To strike the right balance, organizations should adopt a strategy that embraces incremental changes rather than abrupt shifts. This approach allows for the assimilation of new trends and metrics without sacrificing the consistency that the audience relies upon.

  • Continuous learning culture: Organizations must foster a culture of continuous learning and professional development within their analytics teams. This enables data analysts to explore new trends and methodologies while evaluating their applicability and impact on existing processes.
  • Piloting and testing: Before implementing new data trends and metrics across the organization, piloting and testing in select departments or projects can provide valuable insights and feedback. This approach allows for fine-tuning before a widespread rollout.
  • Data transparency and education: Communicating the rationale behind changes in data interpretation and metrics to the audience is essential for building trust and understanding. Providing education on new methodologies ensures that stakeholders are on board with the changes.
  • Strategic alignment: Ensure that any changes in people analytics align with the organization’s strategic goals and overall business objectives. The focus should always be on using data to drive informed decision-making that supports the company’s mission
Planning a people analytics revolution? Use an incremental change method instead

The rapid evolution of people analytics: The need for incremental and continuous learning

In recent years, the field of people analytics has seen rapid advancements. Innovations in artificial intelligence, machine learning, and data visualization tools have revolutionized the way organizations collect, process, and interpret employee-related data. These new tools enable businesses to identify patterns, forecast future trends, and optimize their talent management strategies. However, the pace of change also brings challenges.

To stay relevant and competitive, organizations must invest in learning and adopting the latest techniques and methodologies in people analytics. This means staying abreast of emerging technologies, best practices, and industry standards. Failing to do so can result in a competitive disadvantage, as organizations that embrace cutting-edge approaches gain valuable insights into their workforce, leading to better decision-making and more efficient use of resources.

Consistency in data interpretation: The value of trust and understanding

While staying current with trends is essential, consistency in data interpretation and presentation is equally vital. When the audience is familiar with a particular way of analyzing and presenting data, sudden changes can lead to confusion and undermine the trust in the insights provided. Employees, managers, and executives need to be able to rely on the accuracy and stability of the analytics they receive to make informed choices.

Consistent threads and views in people analytics create a common language across an organization, allowing for effective communication and collaboration. Moreover, when analytics consistently highlight specific metrics, trends, or areas of concern, it becomes easier to track progress over time and identify long-term patterns and opportunities.

The Innovator’s Dilemma: Balancing innovation and stability

How many times do you hear stakeholders (or perhaps you are one) saying you want more? More data, different views, additional analysis, new metrics, predictions, and on and on. Then, seemingly in the next breath saying the information they already have is overwhelming.

It’s a consistent dilemma I’ve run into over the past 15 years in this space and unfortunately, I’ve yet to come across a silver bullet solution. Instead, I’ve borrowed some concepts from the famous book, “The Innovator’s Dilemma” to offer some insights on managing the delicate balance of staying current in people analytics while preserving consistent views.

Clayton Christensen’s renowned theory, “The Innovator’s Dilemma,” provides valuable insights into managing the balance between staying up to date with trends and maintaining consistency. According to Christensen, successful companies can fail when they focus too heavily on their existing products or services and overlook disruptive innovations.

In the context of people analytics, this dilemma manifests when organizations become too entrenched in their current methodologies and resist embracing new data trends and metrics. The fear of destabilizing well-established systems may lead to a reluctance to explore innovative approaches, thus missing out on valuable opportunities for growth and improvement.

On the other hand, constantly shifting approaches and metrics can create confusion and hinder the ability to derive meaningful insights. Organizations must, therefore, strike a balance between embracing innovation and maintaining stable and reliable data interpretations.

An incremental approach to future changes

Staying up to date with current trends and metrics in people analytics is vital for organizations seeking to remain competitive and optimize their workforce. However, maintaining consistent threads and views in data interpretation is equally crucial to build trust and facilitate effective decision-making. By drawing on “The Innovator’s Dilemma,” organizations can embrace innovation while ensuring a balance that supports long-term success. Through a strategic approach that emphasizes continuous learning, incremental changes, and data transparency, organizations can navigate the dynamic landscape of people analytics and stay ahead in today’s data-driven world.

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