Change Management Skills Are Essential To Data-Driven Success
Change isn’t always a breeze, but it doesn’t need to be hard.
Three Key Sources Of Data Resistance
Two things that are intrinsically bound to one another.
A change in data often catalyses changes in other areas to occur. Data can represent new approaches, and/or mindsets, that were previously unfamiliar to many businesses. Additionally, data insights sound (and are) great. However, oftentimes organisations find themselves unprepared for the steady stream of insights and the influence that they can have on the way that a business operates.
So you can better understand the pushback that data often generates – here’s three primary sources of resistance:
3 Sources Of Data Resistance...
1. Cultural Resistance
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
2. 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 recognising 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.
3. 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 organisation.
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 organisations, 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 organisations 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.
Change doesn’t have to be difficult…
Simply put – change management can be described as a set of people related strategies and tactics which can help shift behaviours and mindsets. It’s an unavoidable reality for anyone who works in data.
Change management is a huge subject in itself.
Here’s 5 tips that can help when steering data-driven change:
1. Lead By Example With Executive Sponsorship
Without executive sponsorship 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.
2. Fostering A Collaborative Relationship With Your Teams
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.
3. 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, organisations need to offer data literacy training that is tailored to an individual’s competency level. If your employees lack the right data skills, your data initiatives will continue to struggle to get off the ground.
4. Deliver data-driven quick wins.
To build momentum with your data initiatives, it’s important to deliver quick wins. 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.
5. Communicate to build and inspire
You must create a communications plan for each data initiative that outlines the key audiences, messages, channels and cadence. It’s imperative that people know how to share insights effectively so that they can inform decision-making.
Data holds unlimited potential for organisations that are seeking to improve their business performance, reduce costs, grow market share and innovate. Companies have spend a lot of money on technology and staff to achieve these objectives. Yet, despite these investments, most organisations 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.