Tip 1. Organize feedback
The number one tip for data-driven working is organizing feedback on an organizational level. How can you ensure that people feel like they’re in a safe environment to learn, make mistakes, and say what’s on their minds?
They also have to be able to talk about each other’s performance or their behavior towards customers. It’s about attitude and mentality, with the goal of helping each other.
Creating a healthy feedback culture is one of the hardest things to do for many organizations. Whether they struggle with it or not is the question – that would require it to be on their minds in the first place. The problem is much simpler: most organizations or managers don’t even understand the importance of feedback.
Tip 2. Take responsibility
It’s shocking to see how many people in organizations pass the buck. They will say others – internally or externally – have to do something first, or something else has to happen before they are willing to commit to change. We’ve led various projects where people said things like “IT has to do X first”, “IT has to improve the system first”, et cetera. That costs a lot of energy.
Do you always look at others first, and do you make decisions based on that? Or do you say “I’m going to move regardless, and it would be useful to get help from X department.” The question is: do you wait for someone else, or make the first move? Make sure to act from your own sphere of influence and expand it as much as possible.
As soon as you start passing responsibility off to others, you’re no longer talking about teamwork, but about creating silos within the organization. Everyone stays on their own little island. There’s no sense of team spirit. The feeling of “we’re going to solve this together” is missing across the organization.
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Tip 3. Think holistically
People tend to have trouble viewing all aspects of the organization as an integral whole, including process management, data integration, information management, IT, marketing, HR, et cetera. The third tip for data-driven working is to think of the organization as an integral, cohesive whole. Think holistically.
Integral vision largely comes down to process thinking and plays a key role in processes like Total Quality Management (TQM). The same thing that goes for aspects of the organization goes for the people itself. People have to experience that they’re an integral part of the organization. To do this, people have to be able to rise above their individual labors and be able to see what happens in the entire process.
Only when that integral vision is present can you expect people to think about the business as a whole, and their learning will coincide with the needs of the entire organization. As they get a greater overview, people will realize which tasks keep coming back, which tasks would be better automated, and which activities they could pass on to the customer, for example. You need an overview of the whole to reveal innovations like “self-service through an app”.
Tip 4. Increase the willingness to change
Successful data-driven companies know that the organization can look different tomorrow than it does today. Many organizations are dominated by the classic fear of change. They brace for every change and wonder what else is going to be messed with. Yesterday we did it like that, today we do it like this, and tomorrow we’re going to do things differently than today.
It helps when people realize that they’ve been completing PDCA cycles their entire lives. By supporting that change with data and doing it faster, more frequently, and better, the learning process becomes ever more accurate. The adjustment potential of people and organizations increases more and more.
Tip 5. Embrace transparency
Transparency becomes the standard for change. The data reveals how things really work. In many companies, there’s a fear of transparency. But embracing transparency is a must in order to implement continuous improvement cycles.
Data-driven working ensures a self-cleaning and self-improving system
Data-driven working thus ensures a self-cleaning and self-improving system. Data transparency is the way to quickly improve the entire process.
A practical example
Take, for example, the routes that patients who suffer a stroke take to the hospital. They are racing against time. The data about patient routes will have to become more accessible and public. If surgeons or neurologists in the future choose not to act with maximum efficiency in emergencies, they will have to justify that. Not just to the hospital directors or the department, but to the patients themselves.
5 recommendations for institutionalizing new behavior
If you want to learn continuously, keep adjusting, and safeguard your improvement culture, it’s necessary to regularly and actively invest in this. The tips below can help.
- Keep looking at your business from a bird’s eye view. Keep an eye on emerging technologies and regularly start a new, large PDCA cycle based on one or two of the promising new technologies.
- Safeguard the continuity of services and your delivery process. Ensure that quality and reliability stay top priorities. Remain in control of the reliability of your process. Ensure that you have a model in which you can determine the ratio of products and services developed from the new PDCA and the products and services delivered in the old, reliable way.
- Select employees based on core competencies that aid the continuous improvement process. Look for employees who are driven by passion, data, conscious control, and autonomy. Keep investing in the development of skills that support that.
- Work on a mindset of improvement and learning by communicating the right stories and also talking about the experiments that have failed.
- In order to institutionalize new behavior, it’s important to keep learning and display the behavior as a leader that reflects the values that you want to transmit to those below you.
A practical example
In Rotterdam, a management group was started to safeguard the long-term goals of the NPRS improvement project. Mark de Kort of the NPRS says: “It was obvious from the start that this project wasn’t going to be a quick one-and-done thing. We’re going to be in this for the long haul. Now we know what it takes, and you can see that after 2.5 years, we’ve achieved a lot of results. But more importantly, it led to an entirely new way of working. We can speak of a genuine culture shift.”
Finally
Institutionalizing new behavior in the culture isn’t a matter of making folders full of competency profiles. It’s what happens in the everyday workplace. Continuous learning is a marathon, not a sprint. Keep in mind what it takes in the long term. If you want to get off easy and say “I’m gonna do this for a year and we’ll see what happens”, you probably won’t achieve much.
Daan van Beek MSc, speaker, trainer and author of the BI & AI book 'Data Science for Decision-Makers and Data Professionals'. He is the CEO of the Passionned Group and you can follow Daan on Twitter.
