When it comes to implementing a data strategy, having a false start can be challenging and expensive to overcome, and finding your way back to trusting your data might prove a more difficult task than anticipated. This is why it is important to get it right from the start and don’t miss any steps in the process.
Here are the three major steps to avoid having a false start.
The approach “build it and they will come” does not work. When it comes to data strategy and data platforms, you need to build alignment across the organization. Unless all business functions converge, and stakeholders get behind the process, it could lead to more confusion.
Before committing to implementing a data strategy, make sure you spend enough time upfront ensuring organizational alignment. This is a common mistake we see many customers do: they rush the process and miss important steps. Before embarking on this journey, you need to know where and how you will drive the ROI, as well as have a very strong plan for change management.
It is important that people within the organization know how to use the platform, tools, etc. Part of change management also includes measuring and communicating success. It is paramount to continuously measure the value being delivered, and communicate and evangelize the process.
Enterprises now generate unparalleled amounts of data, especially with the recent surge in digital transformation. This also means that organizations need to handle a lot of dark data and external data sets that everyone wants to use.
The challenge for many companies that follow a generic data strategy is what data they should keep, what’s valuable, and what’s just a waste of storage and effort. Unfortunately, these companies don’t really know the value of any data until later, so they store all data.
It is important to think in advance how you will make the platform usable, it cannot be just a huge kitchen sink of data. It has to be easy to discover and easy to use.
It is extremely important to have three key ideas in mind to make sure the platform and data strategy can succeed:
Have clear definitions of personas who will use the platform.
Ensure the platform has the right kind of solutions and capabilities to help fish data among all its complexity.
Shield people from the complexity with the right kind of tools.
Build Trust in Data
Companies should always try to build trust in data, and see the potential of what it can deliver. Trust in data can have three different elements: purely operational – to ensure the quality of data, data governance, and data security.
Ensuring all of these three together is essential. You have to make sure you’re consistently reinforcing trust in data and include elements of responsibility to avoid breaching any ethical uses of data.
It’s important to know that once you have a false start, it’s very easy to lose trust, and the way back to step 1 is quite uphill. Some of the technology investments for a good data strategy are indeed expensive, and it requires a lot of organizational alignment, but in the end, it depends on how you run your business to make it work and truly deliver value.
Sandhya Balakrishnan leads the Solutions and Go-to market expansion for Data Analytics & Engineering practice. She advises CXOs on their Data & Analytics Strategy and implementation best practices. She has led many of Brillio’s large Data / Analytics transformation initiatives.