Optimizing Your Position in the Race to "Data-Driven"

Optimizing Your Position in the Race to "Data-Driven"

And that has largely come down to data “know-how,” or the knowledge, skills, and capabilities to transform data into valuable insights.

In the current business landscape—characterized by rapidly changing customer and workforce expectations, as well as unprecedented market, societal, and environmental considerations—the need for companies to become data-driven has become more urgent than ever. Data has the power to help leaders and teams make informed decisions, spot trends and opportunities, understand customer and workforce behaviors, mitigate risks, and drive positive outcomes and growth. For these reasons and more, delaying action in the race to “data-driven” is no longer an option for those who seek to stay ahead of the curve.

Global workforce challenges persist and new ones emerge while organizations face pressure to do more with less due to constant recession threats. These factors create unique challenges and opportunities that demand flexibility and adaptability.

This places a new mandate on leaders: Don’t double down on everything, but be prepared to accommodate anything. To meet this mandate, data is the single reliable tool that leaders can trust to guide them through uncharted territory.

But the race toward becoming data-driven cannot be won with data alone. To compete, an equally pivotal success factor is the ability to effectively harness data through internal know-how.

Take a page from tech

Workforce technology know-how has long outpaced peoples’ ability to tap into data and produce actionable insights. Bias, bad data, and distrust caused missteps, and technology widened its stride.

Drafting off technology, many organizations (particularly those that grew into success quickly) didn’t pause to invest in their data capabilities. And up until this point, organizations have grappled with inadequate or poor-quality data, which made the transition to a data-driven approach seem daunting, impractical, and ineffective.

But the tides have turned, and we now have access to robust, dependable data that is easily accessible to all stakeholders, and not just designed for end-users. Many organizations are now equipped with advanced technology and tools that enable them to collect, analyze, and interpret vast amounts of data from a range of digital channels. Additionally, leaders are increasingly recognizing the importance of data-driven decision-making in navigating challenges and disruptions related to the workforce, economy, and more.

And as a society, we’ve been training. Ubiquitously, even unconsciously, we’ve been gaining speed and maturing our abilities to interpret and activate data in absolutely everything we do.

After all, technology and insights have become the metronome by which the rhythm of our everyday lives is set. Our parents use them to connect and receive care. Our society, and especially our children, increasingly rely on technology and data-driven insights to facilitate various aspects of their lives. Technology, for instance, is now a ubiquitous tool for learning, communication, and entertainment, while the concept of success has expanded to include metrics such as online engagement and popularity, exemplified by the use of social media "likes" as a means of measuring one's influence or impact.

As data increasingly becomes democratized, the potential for organizations to empower their people and systems in ways that optimize energy expenditures, increase speed, proactivity, and predictability, minimize risks, and reduce operational drag have never been more attainable. Implementing resource management software can enhance this optimization by ensuring that resources are allocated efficiently based on data-driven insights. Below, we explore exactly how to capitalize on this opportunity by building data know-how.

Put people at the center of your data strategy

Until recently, the concept of a data-driven organization—rife with robots, human-less workspaces, and autonomous everything—felt more science fiction than mission-critical. Then a global pandemic fast-tracked our personal adoption of sci-fi tropes and converted digital novelties into operational necessities.

The technology that props up those robots, human-less workspaces, and autonomous everything are readily attainable. But most organizations aren’t prepared to empower those technologies with the data and insights that generate value and propel them strategically forward.

Here’s what most organizations get wrong: Data collection and insight development is still a very people-centric job.

Tech-empowering, human-inspiring insights don’t come from machine-generated data alone. They stem from an amalgamation of anecdotal, dynamic, and automated sources, and rely on a digitally fluent workforce for successful execution. Becoming data-driven is less about the technology and data and more about the capabilities and know-how of your people. When your employees are skilled at contextualizing data, they can make confident decisions and foster trust throughout your organization, which is a key ingredient to growth.

How to Move from Science Fiction to Reality:

• Get real with how ready you are. A comprehensive assessment, blending subjective and objective data from across your workforce, workplace, and ways of working, provides the required context against which transformation strategies can be developed.
• Hydrate your data lake. Conduct a data health "checkup" periodically to define (or redefine) the data your organization requires and ensure that it has the appropriate attributes to be relevant and valuable.
• Connect your people to the process. Make data the primary means through which everyone's job can be simplified and streamlined. Prioritize building a culture that values collaboration across silos and enables the adoption of robust practices and platforms to facilitate holistic data collection and insight generation. This will position data as a tool that can enhance the effectiveness of everyone's job, rather than as an additional responsibility or burden.
• Make data upskilling a priority. To fully leverage the benefits of data-driven decision-making, it’s critical to prioritize data literacy and fluency across all levels and functions in your organization. In other words, create opportunities for employees to learn about data and develop their skills on the job. This could be done by creating dedicated time and resources for employees to learn and experiment with data, or it might mean setting aside time for employees to attend training sessions, workshops, or webinars focused on data analytics and interpretation. It could also involve encouraging employees to experiment with data in their day-to-day work (i.e., analyzing customer feedback, tracking website traffic, etc.). In addition, organizations can integrate data into their Learning & Development (L&D) programs to ensure that all employees have the skills and knowledge needed to make data-driven decisions. This might involve creating specialized training modules or courses focused on data literacy and fluency, or incorporating data analysis into existing training programs. It's important to note that data upskilling is not a one-time event, but rather an ongoing process as the organization's data potential increases. Therefore, organizations must be intentional and consistent in their efforts to promote data literacy and fluency across the organization, and continuously evaluate and improve their data training programs to ensure they remain relevant and effective.
• Trust your people’s intuition. Establish the structures, tools, and training to standardize employee-led sanity checks designed to weed out biased or dirty data and round out insights.
• Foster a symbiotic relationship between your workforce and your insights. Prioritize the insights that level up individual roles into decision-making, higher purpose, data-generating functions. Additionally, encourage (and make the space for) your workforce to identify and consume data in ways that generate value. 
• Seek insights in full color. Data is good at telling the truth about one moment in time, in one small slice of a dynamic system. Companies must expand that aperture of truth to move beyond black-and-white, moment-in-time data to full spectrum, full-color insights.
  
  

Harness data and insights across your end-to-end transformation strategy

Organizations worldwide spent $1.8 trillion on efforts to digitally transform business practices, products, and organizational structures in 2022. On average, we know that about a third of those investments—$600 million—failed to meet goals and generate value.

The ways organizations are becoming data-driven simply aren’t working, and our recent research spotlights at least one reason why: While data and insights are often used to inform an initial strategy, companies aren’t harnessing the power of data across the end-to-end transformation journey.

The irony is this: Organizations need good data and insights to become data-driven. Good data begets better data; better data begets precise insights; and precise insights beget efficient, proactive, valuable, and lasting change.

How to Overcome the Irony of Data’s Role in Advancing Data-Driven Transformation:  

• Enable employee capabilities and capacity. Identify and automate commoditized tasks to free your employees’ capacity. Then reskill, upskill, and activate those employees to support the development of insights that are high quality, trustworthy, and continuously generated to inform strategic pivots and progress across a transformation journey.
• Build monitoring and measurement into the project plan. Seamlessly integrate these reflection points in ways that facilitate continued forward momentum and prevent blind implementation. Utilize a tool that ingests data from various sources to generate insights that can be monitored and measured.
• In lieu of historical context, lean on traditional data-gathering methods. You are building something completely new, and there is no historical data against which to judge progress. However, other valuable data and insights are there for the taking. Consider bringing quantitative data to qualitative conversations and interactions for a deeper understanding of what drives behaviors, perceptions, and motivations. And while you wait out data’s journey to becoming more accurate over time, employ traditional feedback and insight development methods to establish customized baselines and measurement tools.
  
  

Don’t skip critical developmental milestones

Artificial intelligence (AI)-powered automation and innovations, like ChatGPT, are irrefutably compelling. Yet for most organizations, the application of automation should be less compelling and more commoditized. At least for now.

Before large-scale AI investments, companies must get good at the foundational determinants of a data-driven culture. They must develop the workforce capabilities to produce near-perfect data and bespoke insights, and the cultural trust to let those insights lead. And they must weave data-driven practices into every aspect of decision-making and strategy development in ways that are normal, not novel. After all, access to data empowers companies to identify the most relevant, beneficial, and supportive trends for their overarching mission.

How to Establish Digital Connective Tissue, Not AI Band-Aids:

• Enable your leaders to move from thinking to knowing. A data-driven culture starts at the top, with leaders who practice and expect data-driven decision-making. Quality data enables leaders to move from thinking to knowing, promoting data-driven norms. And the potential of data-driven knowing is personal for leaders: Data empowers leaders with reliable decision-making, reducing bias and safeguarding their position and the impact of their choices. However, embracing the shift to data-driven knowing also requires leaders to seek and provide proof. For instance, in the context of returning to work, relying on assumptions rather than data can create significant issues. Leaders who backtrack on previous declarations are often forced to do so when data reveals that their ideas are not feasible. Thus, incorporating data-driven decision-making is crucial for effective leadership in today’s environment.
• Prioritize adoption over change. Six in 10 IT leaders say they’re concerned by slow end-user adoption, and how it endangers the return on investment. Maximize ROI with robust monitoring and management practices focused on the degree to which employees have embraced the behavioral and technological drivers of data-driven transformation.
• Automate rote, manual tasks to free human capital. Whether that work entails data strategy and insights development, as noted above, or management and decision-making, your ability to create more purpose for your people will directly correlate to enterprise growth and lay the groundwork for the expansion of automation in the future.

Just as our know-how has evolved, so too must our understanding of the true value of being data-driven. Yes, it’s the key to understanding and serving your customers and employees. Yes, it will optimize and automate rote systems and processes. But most importantly, becoming data-driven enables people and organizations to adapt to change. Prioritizing adaptability—not digitization for digitization’s sake—will fundamentally shift how companies plan, implement, and measure their data-driven transformations and keep pace with technology in the curves ahead.