THE BIG INSIGHTSJOIN US AS A CONSULTANT
Building a Data-driven Culture.
Becoming a data-driven company is often primarily seen as a technical challenge. After all, it requires having a data lake from which to draw data, and an analysis tool to interpret and visualise that data. To set these up, you need engineers, data architects, and/or business analysts. While setting up the data architecture is a necessary requirement, it is by far not sufficient. The most important and difficult part is the cultural shift that has to happen within your company and your people. This is a process where people discover and habitualise using data to make better decisions. This article outlines the key aspects that we found to have positively contributed towards building a data-driven culture within The Big Search.
Deliver a quick win.
Building data infrastructure can be an expensive and lengthy process. This can lead to situations where a significant investment of time and resources is put into data infrastructure, but no user value was generated. In the worst case, this leads to the project being scrapped altogether before any significant value was delivered. Hence it is important to deliver a “quick win” early in the project; Even if the value is not significant, it will help build excitement for things to come and justify further resources going into the project. In the case of The Big Search, this quick win was a simple always-up-to-date overview of all running projects, along with the potential revenue for those projects. While not a massive game-changer, it started to build excitement, like a movie teaser trailer.
There are very different levels at which leadership can demonstrate buy-in, from formal budget approval on one side to clearly demonstrated attention and excitement of the leadership team on the other. At The Big Search, there was clear buy-in, starting with the CEO. This was demonstrated to the whole company by using various dashboards and KPIs during meetings. Every time a report or dashboard was delivered, it started appearing in meetings the very next day. This helped greatly with adoption as it showed the importance of leveraging data to everyone in the business.
Getting the first follower.
Even with leadership buy-in, building enough momentum to shift the company culture can be hard. This task is often given to external consultants or a new team that was hired for the purpose of making the company data-driven. This does not set these people up for success, as they do not have the required strong relationships with departments in the company to shift the company culture. That is why gaining a first follower to buy into the vision you are selling is very important. You can find a great article explaining the concept of a first follower in-depth here.
Engage and train.
Great, you have buy-in from leadership and your first follower. One by one, people are starting to get excited by the change and want to get involved. So what’s next? You need to engage and train your colleagues. Firstly, get them involved in the process - listen to their needs and their worries. Talk to as many of them as possible. By involving them, you increase your chances of their buy-in and get a better understanding of where exactly data can deliver the most value. Next, you need to equip your colleagues with the skills and confidence to start using the tools at their disposal. This is a continuous process, which requires a lot of patience and approachability, rather than running a single training session, but can lead to great results.
To illustrate this with a real example from The Big Search. In the graph below, you can see the trend measuring the usage of one of our new data-related features. In the weeks of July 19th, Aug 9th, and Aug 16th we ran a training session on how to use the feature where the users tried using the feature themselves. Naturally, there is a spike in usage, which drops down again the next week. However, if the trainings are accompanied by continuous support such as answering questions, the overall usage grows slowly and surely. Since August 16 we have not run any trainings and yet the usage has steadily grown week by week.
Ensure there is no loss of trust.
At this stage, momentum for change is growing and people are getting more familiar and comfortable with the tools. Data usage for daily decisions is becoming mainstream and everything is going well. Time to rest and move on to the next project? Not really, as now comes the critical part where the changes and habits are still very fragile. This means that if there is a major problem with the data validity or accuracy, it can very quickly erode all trust in the data and undo all the work you have done. Imagine a department head making a decision based on some information you provided, only to find out later that the information was wrong. You will have a hard time convincing that person to trust the data ever again. If such an incident occurs, it is important to resolve it as quickly as possible. Be transparent on what went wrong without blaming anyone, and explain how such a situation will be prevented in the future.
Data should empower people, not police them.
This last point may depend on what kind of data culture you want to build, but at The Big Search we want employees to be empowered by data, not policed by them. Quite often, data is used to set performance goals and track people’s performance (such as in Amazon Warehouses). While this can increase performance, it does not generate a healthy data-driven culture (at least not across all levels of the organisation). People will search for a way to game the system, and thereby skew the data you are collecting. This can be tackled by more robust data collection, but can quickly turn into a game of whack-a-mole. If instead, you set up data to enable your teams to do their work better and faster by removing mundane tasks, you will develop a healthy culture full of innovation and cooperation. For example, most of the projects we are currently working on came as suggestions directly from people across the whole organisation who are eager to use data and insights in their work.