Change is never easy. We often resist it even when we know it can lead to positive outcomes. Journalist and author Sydney J. Harris summed up our awkward relationship with change when he stated, “Our dilemma is that we hate change and love it at the same time; what we really want is for things to remain the same but get better.” Unfortunately, it’s not possible to progress or evolve without changing your strategies or tactics.
Today, data is posed to fundamentally transform the way businesses operate; however, it hasn’t done so at the pace that everyone anticipated. In the NewVantage Partners (NVP) 2022 annual executive survey, only 26.5% of surveyed companies reported they had created a data-driven organization. Over the past six years, this percentage has fallen from a high in 2017 of 37.1% to a low of 24.0% in 2021. Instead of seeing more companies becoming data-driven, almost three-quarters of companies are still struggling to embrace data.
As the adage goes, you can lead a horse to water, but you can’t make him drink it. The same applies to data. Most organizations have made significant data investments, but that hasn’t led to their people using data on a more consistent basis. With 83% of CEOs wanting their organizations to be more data-driven, companies are posed to experience significant changes in the years ahead. Each organization that hasn’t yet become data-driven must figure out how to overcome internal resistance before its competitors do.
Three key sources of data resistance
Data and change have a deeply intertwined bond. One of the challenging aspects of data is that it represents both change itself and spurs it to happen in other areas. First, many organizations haven’t been accustomed to working with data on a regular basis. It represents a new approach or mindset that is strange or unfamiliar to many businesses.
Second, the insights that emerge from the data can sometimes necessitate unexpected changes across different functional areas. Many organizations are not prepared for a steady stream of insights that can influence how they operate. To better understand the pushback that data often generates, here are three main sources of resistance:
- Cultural resistance. In the latest NVP survey, 91.9% of executives said cultural obstacles were the greatest barrier to becoming more data-driven. When individuals and teams are expected to start using data when they haven’t in the past, the existing culture will often fight such a change to the status quo. In a recent report by BARC, they identified two main groups that resist data culture: longer-tenured employees who are less open to change and less data-literate employees who feel intimidated by data. Without a strategy and plan to help these two specific groups embrace the new mindset, it’s going to be difficult to build momentum with your data initiatives.
- Procedural resistance. While some individuals may not have any issues with data in general, they may have reservations about how it is used in key business processes or specific scenarios. For example, bank employees may disagree with attempts at using credit data and AI to streamline loan applications. Rather than recognizing the greater productivity, increased accuracy or faster turnaround times with automation, the employees may be skeptical of how reliable and efficient it really is. Rather than embracing the new data-driven process and helping refine it over time, the team may wait for it to fail so they can keep doing things the traditional way.
- Decisional resistance. The main purpose of data is to inform key business decisions. Even when data-savvy people are presented with new insights, they may still reject them if they don’t align with their existing viewpoints or agendas. Some insights can be hard to accept, especially when they highlight problems or mistakes. For example, an HR director may not enjoy hearing from an analyst that her new retention program isn’t performing well. A bruised ego may cause her to outright reject the information when she could have leveraged it to find ways to improve the program. If your people aren’t willing to be open-minded and learn from the numbers, analytics will have no measurable impact on your organization.
As you can see from these examples, data faces a steep uphill climb with multiple forms of resistance. Even if you can convince people of the importance of data, they may not like how it’s applied or what it tells them. When data represents a formidable change for many organizations, it’s surprising to see that the fields of analytics and data science haven’t paid more attention to change management. Ultimately, we need people and organizations to adapt and embrace data so that it can inform decision-making. More work must be done to lead and manage the change that is generated by data.
Five tips for leading and managing data-driven change
A simple way of looking at change management is to view it as a set of people-related strategies and tactics that can help shift behaviors and mindsets. It’s an essential skill set for everyone who works with data from the Chief Data Officer (CDO) down to junior analysts. Data leaders will be primarily focused on cultural and procedural resistance, whereas analysts may only deal with decisional resistance. The scope will differ across roles, but everyone plays a valuable part in the transformative process.
Change management is a deep, multi-faceted subject, and there is a vast body of work on the topic. However, I’d like to offer five tips that can help with leading and managing data-driven change:
- Secure a good executive sponsor. According to change management firm Prosci, the most important success factor in driving change is an effective executive sponsor. Without one, it will be impossible to generate sustainable change. An executive sponsor can help win support and buy-in at the executive level but also lead by example in using data to inform their decision-making.
- Foster a collaborative relationship with business teams. From time to time, I’ve seen data teams operate in a vacuum with only limited interactions with business teams. This is a recipe for failure. When you can build a strong working relationship with business teams, you ensure the data is aligned with their needs. In the process, you will also make them co-owners of the data initiatives, which is essential to adoption and buy-in.
- Offer data literacy training. For many business managers and employees, data can still be very intimidating. To increase people’s comfort level with how to use and communicate data, organizations need to offer data literacy training that is tailored to an individual’s competency level. Tableau reported there is a significant gap between what leaders say their companies offer in terms of data skills training (79%) and how many employees report they have received what they needed (40%). If your employees lack the right data skills, your data initiatives will continue to struggle to get off the ground.
- Deliver data-driven quick wins. To build momentum with your data initiatives, it’s important to deliver quick wins. Rather than waiting for a long-term payoff, potential skeptics or detractors need to see faster returns. When people get a taste of what’s possible through real-world improvements, it becomes easier for them to envision what the future state with data looks like and get on board with the changes.
- Communicate to build and inspire. Communication is a critical component of any successful change management strategy. You must create a communications plan for each data initiative that outlines the key audiences, messages, channels and cadence. In addition, with data and communication, it’s also imperative that people know how to share insights effectively so that they can inform decision-making. In a recently published white paper, I explore how data storytelling can help organizations to build data cultures by fostering data-centered dialogue and developing data literacy skills in the process.
Data holds unlimited potential for organizations that are seeking to improve their business performance, reduce costs, grow market share and innovate. Companies have spent billions of dollars on technology and staff to achieve these objectives. Yet, despite these investments, most organizations have made limited progress in their data journeys and are still using data sporadically and selectively. If companies continue to overlook the people-centered challenges associated with adopting data, most of them will be no closer to becoming data-driven in the coming decade.
Real change begins when data-savvy leaders and data professionals recognize the influential role that change management must play in forging data-driven organizations. Without it, the promise of data-driven transformation will remain just another technobabble pipe dream. Business author Philip B. Crosby said, “Slowness to change usually means fear of the new.” To accelerate data-driven change, we must replace fear with wonder and excitement at what data has to offer—both individually (“what’s in it for me”) and organizationally (“what’s in it for us collectively”). This will only be possible if you fully commit to actively leading and managing the change that data creates within your organization.