Managing Change: Data-Driven Decisions
The Data Gap Is As Big As Ever.
The last few years have been dominated by talk of digital transformation, data adoption and of course AI. But have companies really made any progress?
A 2023 survey from New Vantage Partners to Fortune 100 companies compared answers from 2023 to 2019 and found that:
Just 23.9% of executives reported that their companies have created a data-driven organisation, actually down from 31% four years earlier.
Only 20.6% reported that a data culture had been established within their companies, down from 28.3% four years earlier.
While 39.5% of executives reported that their companies were managing data as a business asset, that was still down from 46.9% in 2019.
Those results are quite surprising! They paint a picture of a gap which is expanding between what companies are hoping to achieve with their data and the realities of today. That, whilst everyone is talking about creating value from data, few are achieving it. So how can this gap be bridged?
One aspect that is often overlooked is change. For most companies a ‘data-driven culture’ is a change from the norm, even now. And where there’s change, there needs to be management. Change management is the structured approach employed by organisations to guide individuals and teams through these transitions. So how would it apply to data projects?
Sometimes, it’s useful to take a step back and consider the wider picture. Why do you need to change? What are your key objectives? These seem like basic questions but it would be fair to say that a lot of managers have put their analytics teams under pressure to adopt AI for fear of being left behind, and not necessarily with a strong use-case for their business.
When we think of data, we often think solely of “making more informed decisions” but this is rarely the only benefit. Think about benefits the change will bring, whether they be financial in nature, understanding your customers better, improving processes or learning and growing. While making better decisions is still valid, what decisions do you want to impact, how will data be used, how big is the opportunity cost in not embracing data?
In order to understand how change will affect your organisation, you need to have a decent understanding of the current processes and practices in place today and start thinking about what a new process may look like.
In order to enact any kind of change you will need sponsorship at the highest level. When mapping out your stakeholders, it is important not only to think about who has the biggest influence in terms of approval or blocking, but also who has the biggest interest in your project. These are the individuals and teams who may be directly impacted by the implementation of data. We would generally advise involving both upper management and IT in the process as early as possible, as they are likely blockers to any implementation later.
Of course in managing stakeholders, a number of challenges arise:
- Stakeholders may not know what they want.
- What they want vs what would be most useful is not always aligned.
- What they want vs what’s possible is not always aligned.
- People are generally resistant to change.
Data leaders need to guide everyone as to what initiatives will have the biggest impact, what’s possible and the process to get there. This is no small task but at the very least you need to know which area of the business you will focus on, what the short-term goals are, and a rough idea of the steps to get there. A requirements file is often a good place to start as this can help to scope the project, map out data points and understand deliverables.
With your stakeholders onboard and your plan in place, you can begin to implement your data project. It’s crucial to clearly communicate a vision of what you want to achieve and the rationale behind this. People may find change uncomfortable, but they will accept it (or at least be more willing to accept it) if they can see the logic behind it. This can be greatly enhanced if you can point out how their own lives/jobs may directly improve as a result.
Many of your colleagues are not data-savvy people. To them how analytics works is a complete mystery and they have no reference in terms of timelines. Waiting months with no discernible outcome may be difficult for them to accept. This is why we always advocate for an iterative approach, delivering value in smaller chunks so that stakeholders can begin using the data solution. That might mean for example, starting with a master dashboard before you get into more granular insight.
The important thing to remember though is that the end of implementation is NOT your data product or dashboard or report going live, it’s only when your change has stuck and people have stopped doing things the old way and adopted a data-driven approach.
It needs to be very clear what you want people to do and why. People will quickly slip back to their old ways of working unless you’re willing to monitor and enforce the change. New practices need to become the norm, especially if you’ve put the effort into providing training and support. Consider how you can utilise internal comms, competitions and even good-old fashioned posters to get people excited about using data when the new systems go live.
Analytics projects are about more than just surfacing numbers, they are about changing the way people work and make decisions. With any change it’s important to remember that you can only go as fast as the slowest person. Take the time to map out and understand today’s processes and their challenges, implement data in smaller pieces, communicate the journey you are on and know that your job isn’t done until everyone is regularly using your solution.