Corporate transparency, flat organizations, open book policies, etc. are terms executives and entrepreneurs learn about all the time. As the corporate world shifts towards a more open culture, the demand for open data and insights have increased dramatically. This shift has helped the overall corporate strategic planning and management process–easing the alignment of business activities towards a series of goals. Being transparent top down aligns the culture to sail towards the same North Star. (Verne Harnish wrote a great book, Scaling Up, which has a section that talks about the company mathematics and creating scoreboards)

The growth of corporate transparency is not only important internally, but externally as well. Corporate certifications like B Corporations certifications (B Corp), require companies to provide a transparent view on their social conscious efforts to the general public. Achieving the certification is one step of the process; the true goal is to show the world how and why the certification is truly deserved.

How does data visualization play a part? Data Visualization helps reveal insights and patterns that aren’t immediately visible in the raw data. Here’s an example of an internal scoreboard that showcased website analytics performance:

Here’s the process on how to get it done:

Step 1: Perform Data Discovery and Determine The Story (From our previous blog post (Show Your Data Truth)
Before this step it is easy to underestimate the effort level it takes to pull the best insights from the data. Data manipulation products like Tableau, Domo, Pentaho, IBM’s Many Eyes, and R, among others, make insight extraction that much easier to gain understanding of data using a visual medium.

The key is to start with a simple portion of your data and to start pulling basic insights to visualize and correlate with each other. This process leads towards a compound series of questions, which helps provide an overall vision to the end product. We see the effect during our discovery process, which leads to unforeseen avenues for data intelligence.

Step 2: Data Infrastructure Setup
Data infrastructures can be simple or complex depending what the end goal is. Many clients prefer to go the route of complete data integration in order to centralize their data repositories. Technologies such as Hadoop have helped by unifying disparate data sources, but other options such as data cloud environments can help produce API’s for future product deployments. Why is this important? Accessibility of data is an important foundation not only within the context of dashboards, but also the possibility of branching out to other products.

Step 3: Product Design & Development
Wireframing, prototyping, and application development are the main engines to transform an idea into a final product. Products can range from static presentations/reports to full interactive applications. Mobile, tablet, TV, and workstation platforms can all be mediums to help deliver the final product. The secret to a great end product is how well the data story is conceptualized. If the story is weak then the end product will also suffer. It doesn’t matter how good the lipstick looks on a pig…it’s still a pig.

Step 4: QA & Product Release
The best part of any project is to get it finalized and released for all to see. All data gets verified for accuracy, functionality testing (if applicable), application flow (if applicable), design testing, and remaining items are all completed. The end result is an engaging visual product for all intended audiences to see and use.

The word, “Transparency”, is a legacy word from the early years of the social media marketing movement. Our belief is that transparency is playing a larger role in all industries and it’s because of the data available to us. The biggest challenge in revealing insights from this data is to ensure that the data story is thought out and whatever the end product is, it is truly successful in delivering that story.

How can we help you with Corporate Scorecards and Data Visualization?