In our last article, we defined data quality as a central part of a successful BI strategy. We also explored three specific areas – trust, time, transformation – where data quality plays an important role. But establishing a successful BI strategy is not only about securing data quality but also about creating an organization-wide understanding of all BI assets and components. Someone once told me that presenting sexy visualizations is enough to keep the user and business satisfied and to drive your BI strategy forward. But this a very short-term fix that only really looks at part of the challenge.
Sexy visualizations just aren’t enough
It is easy and understandable that a BI strategy often focuses on building visualizations and easy-access applications. The human being is driven by easy-to-understand graphics and it is a natural first step in a project roll-out. But over time, the importance of actually understanding what lies beneath the graphical surface will become much more important. A trusted BI environment will scale and drive analytics adoption – a non-trusted environment will get stuck and the user will find other ways to get the information they need.
Establishing long-term BI interest and engagement
This article will focus on the assumption that building data trust is a necessity when it comes to establishing long-term interest and engagement from business users. To achieve this, there are a few different areas to focus on:
Trust stems from a combination of data quality and data understanding. Being able to answer questions such as what is the definition of a specific field, what is the description of a central KPI and how should it be used and interpreted, etc. plays a huge role. Once again, a sexy visualization will make a nice first impression but it will never last if the user doesn’t fully understand the data and the meaning of the visualization.
Put the business user in a position where they have full control of what data they are looking for — where they know exactly where it originates, how has it been transformed between the data source and the visualization, etc. The more insights they get, the easier it is to build trust.
Create an environment where the business users can discuss the data, the metrics, the apps and share ideas, thoughts, etc. Collaboration helps establish individual trust and also to spread trust throughout the organization.
Just as the quality of the data is important, it also similar important that the information around the data is correct. The only true way to secure that this is the case is to focus on automation in all steps.
What can you do to build a culture of data trust?
So, what do you need to do to take the necessary steps toward trust?
- The answer is not only in the data and the quality of the data – you must also focus on the metadata, meaning the components, steps and processes that build your BI environment. To have full control of all your metadata and the data lineage is a key success factor for the future.
- Increase the involvement of the business user – give them the correct tools and possibility to get the needed insights to build solid trust and understanding for the BI visualizations and components.
- Focus on the whole data value chain – from data creation to data consumption. All parts matters and the key is what lands in the hands of the business users.