Throughout the past four years of Data Business, our participants have increasingly understood the importance of being visual when they are trying to convey their understanding of complex problems. While on this journey, participants have also realised that the capability to translate verbal/textual data into a visual artefact is not well developed in most people, most notable themselves (the business executive). This represents a significant challenge because breaking down complex problems most often requires an ability to “see” the problem and seeing the problem requires us to visualise its components so we can share our understanding with others. On the Data Business programme, understanding this translation of verbal/textual data into visual artefacts is extremely important for unlocking business value from business data, and we achieve this through relational data modelling using our canvas

In business today there are many data black boxes. By data black boxes we mean business applications with associated data repositories that no one truly understands. By truly understands we mean no individual or group has a full appreciation of the data models that dictate the structures of the data in these repositories. By data models, we mean the relationships between the business things of interest. By business things of interest, we mean the master data of the business. However, our applied research activities on the Data Business programme inform us that when executed effectively data modelling can impact positively on the business – from the shop floor to the boardroom. Soundbites from business executives on the use of data modelling have been extremely positive, for example:

• “I didn’t realise data modelling is as much an art as it is a science.”
• “This is a new way for me to look at the business.”
• “I think we have overcomplicated the relationships between the business things – simplicity is the key.”
• “Doing data modelling is exposing the cost of data silos in my business.”
• “I wonder who performs this modelling role in my business today.”

So the fact that a business is supported by many different business applications (aka data black boxes) can suggest that the data picture (aka data model) may not be very well understood by the business, or indeed it may not be as simple as it possibly could be. This data complexity is further compounded by the semantic differences that exist across business units when defining the same business thing of interest (e.g. a customer or a product). Our Data Business experiences tell us that by taking part in data modelling workshops, business executives can experience the value of thinking differently about their data and essentially draw a more appropriate data picture.

However, in the Big Data era, relational data modelling has been somewhat disregarded as to its importance, but this is simply because it has all too often been misunderstood by business executives as to its business value. A point often not appreciated is that relational data modelling does not simply mean relational databases; they are two very separate things! To be clear, relational data modelling is more concerned with the fact that the business understands their critical business data through the lens of a relational data structure (the relationships between the business things of interest). Within Data Business we champion a mindset that promotes the business value of relational data modelling as being a low tech, low cost, collaborative and people-centric activity. The data models that are designed are canonical (independent of any existing systems) and low fidelity. To provide an example, three business executives (completing the MSc Data Business) have calculated the business value of their respective A3 sized, paper-based, business-oriented, relational data models, designed using our canvas. These valuations have come in at €1m, €10m and €16m. So data modelling has an important role to play in unlocking quantifiable business value from business data.

To conclude, our applied research experiences (both inside and outside the Data Business classroom) have provided ample evidence that the design of a data model (data modelling) by business executives is an effective way of visualising complex problems through the translation of verbal/textual data into visual artefacts. Ultimately, a data model designed by business executives targets the complexity of business data and remember a picture is worth a thousand words!

Tadgh is a lecturer and researcher in Information Systems at University College Cork. With a background in financial services his expertise is in strategic innovation and emerging and disruptive technologies.

David is a Professor (Information Systems) at Cork University Business School (CUBS), University College Cork (UCC). David’s research interests focus on the areas of conceptual/logical data modelling, agility, master data design, theory and theory-building, and redesigning organisational routines through mindfulness.