This could turn into a bit of a rambling rant, so consider yourself warned. One of the challenges we face with digitisation is subjectivity. As a former colleague once stated “data is brutal”. Being able to take data, turn it into information that is analysed to gain insight which we can then form advice for our clients and teams is THE key process that the digitisation of our industry needs to be focused on. When someone announces your model has issues with 33,000 components, that is brutal data, but add in that your model contains 1.5 million components and you get a more balanced view. That is still objective.
Subjectivity starts to creep in through language. Sometimes hampering or even destroying the ability to create any sort of analytical/computational/automated approach. How do I go about finding these blockers? I look for the words below which have always created challenges and, as my blog title alludes to, the cultural/people aspect can block the process and tools stream. So these are some of the words to watch for:
- As necessary
Look through your documentation, your scope, EIR and BEP, even you Standard Methods and Procedures (SMP). See if these key documents contain this sort of language. Really understand where these words have been used and why, how their context can impact objective data creation and collection. With data being firmly on our industries agenda and with more collection and sharing of data, we can and in some cases do, collect as much data as possible to then look for trends, means, norms and ranges. This does allow us to look at what these subjective words mean with regards to data and whether something is indeed measurable. Once something is measurable we can start looking at its value objectively, which for me, is where I want to be in order to be able to leverage data and put it to work.