Joining Up Staff Data: Week Note w/c 11/11/19 – Alpha (Experiment).

The job interview and the idea of doing nothing…

The first part of spring two was mostly about narrowing the field to a more workable set of variables that we could really dig in and focus on. This made sense so that we could ask better and more specific questions to those around us who were helping us to consider the options.

We had lots of fields which was possibly a bit unruly to make the first steps to joining up staff data… so we decided to give our ‘candidates’ a grilling…

And what better way to do that by interviewing them!

We gave each of the possible candidates a persona and interviewed them as if they were applying for the job…

– Why do you think you would be good at this job?
– What are your perceived weaknesses?
– How well do you interact with others?

Were a few of the questions we asked the applicants.

We also cross examined them against what they were suggesting as we got really in to the process… “you ‘say’ you’re unique Ms Staff-EmailAddress, but actually, looking a bit more deeply, we’ve found that you’re not as unique as you think you are – can you explain a bit more about this?”

It was a fun exercise and it really allowed us to explore the possibilities in some depth. Ultimately, the process allowed us to narrow down our working variables to three chief fields:

Staff Email
First Name (job share/work experience)
Surname (job share/work experience)

Having done this, we started to expand our thoughts and direction.

In a workshop including Daro from the Data and Insight Team, it was brought to our attention that a similar conclusion had been reached in an independent piece of work and we were really pleased about this validation. To our surprise and delight, we also learned that a tool had been created to create some data insights that wasn’t a million miles away from where we were headed too.

It was an interesting moment and posed a new set of questions and options that we hadn’t considered before.

One such option was the idea of doing nothing.

Odd one might think, but we wanted to make sure that we explored the pros and cons of every choice.

Could we do nothing? Decide that the many of the success criteria for our project had already been fulfilled?

We weighed it up…

– It would save time
– We could start work on other things
– There were some insights we could derive from what’s been done already

We also explored the other options around continuing:

– What if we sought to take the analysis of this data to the next level?
– Could we ‘piggy back’ on to what had been done and build something else in to in to it?
– Maybe we could re-build something ourselves and see how the two tools compared?
– Perhaps we could test the existing tool rigorously and see if we could spot any flaws?

We had a rock solid discussion where we weighed up the pros. cons, risks, what’s involved, how long it might take amongst our thinking processes.

We also worked through a number of musical genres in our thinking time (with an alarming number of the group knowing ALL the lyrics to Sinitta).

Ultimately we concluded that doing nothing wasn’t an option – the discussion around joining up staff data isn’t going away and so whilst there are questions still being posed, there are still answers to find.

We decided that at this point we would “Piggy Back” on what has already been done to date.

This would include rigorously testing that tool and also looking for further insights that the business is already asking for.

It leaves us in a potentially fortunate position, because if the existing tool proves to be robust, it means that a good chunk of the ‘MVP’ work has already been done and our focus can switch to the second set of questions that we’re interested in looking at.

What insights can we get?
How can this be expanded upon and scaled?
How might we build on what’s been done?
What needs to happen in the business for that to happen?

We look forward to testing and sharing!!

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.