For many organizations, it is still difficult to understand what Big Data is and how it should be incorporated in their business. This is quite understandable, as Big Data offers such radical and disruptive new possibilities as well as requires a dramatic cultural change for many organizations. The past weeks I have been thinking a lot about this and how this process could be simplified. Because when more organizations understand how to embed Big Data in their business, the more it will drive innovation and economic growth.
We know by now that Big Data can have a big impact on any part of your organization. However, when I talk to organizations, I still get a lot of questions how they should start with Big Data and what they should do to become really data-driven.
Well, as it turns out, there is a rather simple five-step approach that could help any organization to datafy their business and processes. These steps are:
Determine the Different Processes to be Improved
Determine the Stakeholders Involved
Turn Connections and Processes into Binary Code
Start Mixing and Analyzing the Different Data Sources
Continuously Improve Your Analytics with Machine Learning
Let’s discuss them one by one:
1) Determine the Different Processes to be Improved
In order to incorporate data into your business processes, it is, of course, important to first determine the different processes we are talking about. What you want to do is to datafy these processes in order to improve them. But if you don’t know which processes are in place, it becomes rather difficult.
So dissect your organizations processes to a very detailed level. Specify each process into sub-processes that can be made into even smaller processes. Make the different processes as small as possible and define each possible step required in a certain business process.
2) Determine the Stakeholders Involved
Each process requires certain stakeholders. Once you have a clear understanding of the different processes that make up a certain business solution or question, you should start to define who the different stakeholders are that are connected to those processes.
It is important to define who these stakeholders are in every step of the process that you have defined. This should give you information about how the stakeholders are linked with each other and how they communicate with each other. The objective is to get a detailed overview of how the processes work, who is involved, when, where and why.
3) Turn Connections and Processes into Binary Code
Once you have a very detailed overview of a process, it is time to turn the different steps and connections between stakeholders into binary code. So, what should you do to digitize the different steps? Because, once it can be captured by data, it can be stored, processed, analyzed and visualized.
In addition, determine what needs to be done to achieve that. What should you change within the different process to capture data? Which data should you capture at all and where can you get that data? Do you need to obtain new data? Can you capture the data internally or should you obtain the data externally, for example via public data marketplaces?
The objective is to turn each single step into data.
4) Start Mixing and Analyzing the Different Data Sources
Once you have been able to turn the different processes and connections between the stakeholders into data, something magical happens.
All of a sudden, you are able to combine the different data sets, mix them with each other, analyze them and obtain great insights that can improve your processes drastically.
For example, in case you want to optimize a certain process and reduce the inefficiencies, you determine which datasets you require, which data you already have and which data sets you need to acquire. Those data sets can then be used to improve the processes by gaining new insights, finding outliers or determining patterns in the processes that indicate certain, potentially unexpected, relationships. The information derived from the analysis will help decision-makers improve the different processes and as such the organization.
The advantage of starting with very small steps within a process is that it remains doable. Each organization that wants to develop a Big Data strategy has to start small and grow from there. This process helps you achieve just that.
5) Continuously Improve Your Analytics with Machine Learning
The final step would be to use machine learning and artificial intelligence to improve the algorithms you use for analysis. When logging what happens during the different processes as well as during the analysis of the different processes, more data is created that can be used to improve the algorithms.
Better algorithms mean better insights, resulting in improved processes. It becomes a cyclical process that ensures a continuous improvement within your processes and as such an incremental improvement in your organization as a whole.
Although this approach is easier said than done, it is something that any organization should start doing as soon as possible. Define which processes make up your business, determine the different stakeholders and connections between them and find out how you can digitize them. Datafied processes can be combined, mixed and analyzed for better results and with ever-improving algorithms, your organization becomes more and more prepared for the Big Data era ahead of us. Good luck and don’t hesitate to contact us if you have questions datafying your business.