Storytelling in Data
Today's guest post is from Doug Hudgeon, Director of PitchMap, and a long-time Procurement blogger. Back in the day, he authored a vendor relations blog on WordPress (at hudgeon.wordpres.com) and more recently he authored the Operating Efficiency blog (at OperatingEffieciency.org), which has now been ported to the PitchMap Blog. It originally appeared on the PitchMap blog yesterday, and is being reprinted with kind permission.
Now that we've introduced Pitchmap, I'm returning to topics on business operation efficiency. Today’s topic is Telling stories in data: Using data to support your arguments
Yesterday, I attended the first Australian IACCM meeting of the year. The two presenters spoke on very different topics, “Clean energy laws and carbon trading” and “Utilities Benchmarking” but both presenters were equally adept at using data to underpin their arguments. Today, data is everywhere and an effective business person must be an expert in presenting their arguments using data. In my view, there’s nothing like a story to make your audience feel that change can happen and a vision can be achieved.
Storytelling in Data
Let’s look at some Pitchmap data to show how data can be used to tell a story. This data compares the procurement processes of three companies (Salamander Logistics, Melbourne Transport and Queensland Trucking) with each other and with an optimised process. The columns in the chart show the cost per transaction: the higher the column the greater the cost per transaction. The type of transaction is shown by the label above the columns.
The first story in the above data is indicated by the red arrow. It shows that Melbourne Transport is spending about the right amount on Vendor Creation processes whereas the other two companies, Salamander and Queensland, appear to be under-investing. This does not say that Melbourne Transport is doing it right, just that they are spending about the right amount on it.
The second story is indicated by the yellow arrow. The story within the data is that Melbourne is better than its peers but higher priced than optimal. Interestingly, the purple section of the column (transaction costs relating to invoice processing) is the same as the optimised process but the green section of the column (transaction costs relating to placing orders) is significantly more expensive. This indicates that Melbourne Transport should be focusing its process improvement initiatives on order placement rather than invoice processing.
The last story is highlighted by the blue arrow. Melbourne Transport and its peers are significantly more expensive than the optimised process. This should serve as a red flag in any attempt to re-engineer this process given that no one is doing it particularly well. It may well be that there is some aspect of expense processing such as regulatory requirements in this industry or geography that adds to the cost of the process and further investigation should be undertaken to ascertain whether this is so.
The keys to successful storytelling
The keys to being able to tell stories with data are four-fold:
- The data must be clearly displayed – preferably on one page,
- The data must show where you are now and where you could be (either by reference to an optimal state or comparison against your peers or benchmarks or all three),
- The data must be sufficiently detailed to make the story interesting, and
- You need to be able to dive into the details underlying the data when your assumptions are questioned.
Doing so will enable you to present a compelling picture (as in the chart above) of what needs to be changed, how it needs to be changed, and what further inquiries need to be undertaken to resolve outstanding questions.
In my next post, I’ll discuss how to collect and present variable data in a compelling manner.