What’s the most important part of a successful project that hopes to deliver strategic business insights and who is the most important member of the team?

Its not the data, its not the tech stack, its not the scientist or the models they’re using. It’s the question asked, and the person asking it.

The person asking the question which starts a project, 9/10 wants to do something, or is leading the team who will. That something, is the only reason they’re engaging with you. Other than your winning personality of course.

If they achieve that thing, then by their definition the project will be a success. If they don’t, then it will be a failure. This is where a disconnect between data creators and consumers often comes about. You work hard to answer every question (so its a success by your definition) and yet your consumers still aren’t satisfied.

Angry Data

A picture of one of my analysts after being told his work “didnt help” despite a whole week of immense effort.

Let me tell you a harsh truth. Your insight consumers do not care…at all…about the work you put into their outputs, unless they work for them. And the truth is, they shouldn’t care. Your job is to help them. Your effort is meaningless unless it equates to achieving positive real-world change.
 
So, if you are answering every question, and this isn’t resulting in positive change? Then you aren’t answering the right questions…right?
 
“Ok fair enough…but its not my fault the questions they ask aren’t the right ones!”
 
WRONG. It is your fault. It’s your job as a data professional to help improve the data culture of your organisation as well as provide insightful analytics. If you don’t help your sales team ask the right questions then who will? It’s not the sales directors job. He’s far too busy schmoozing clients and drinking the expense account dry! I’m kidding of course, he holds some responsibility. But it is part of your job to help everyone start insight projects in the right way by asking the right questions. Especially if you are in a leadership position.
 
Take this completely made up and simplified example;
 
Chad, the sales director, needs some data. Lockdowns over and villa rental prices in Cabo are going through the roof. He needs a bigger bonus this year. He knows you collect data on client spend over the last 3 years so Chad emails you and says;
 
“Hey Data Team, I need that data on client spend over the last 3 years by product type, Thanks.”
 
Chad’s right, you have this data already modelled, quick pivot and its done…perfect. You send it on over. That might be enough! Chad might be toasting the data teams excellence by a pool in Cabo before the year is out. But what if Chad had used a systemised process which led him to give the data team the right context?
 
What if he had told them what he already told them in his email, but also what he wanted to do with the information? And what if the data team got this from the start, and didn’t have to chase him saving time and effort?
 
What if…Chad had requested this information through…dare I say it…Brijj? The simplest possible way to get your consumers to ask the right questions?
 
If he had, he would have used the guided forms to ask the exact same thing he already did in the summary and description. Fine, he’s a busy man, we wouldn’t want to put any barriers up between him and the data team. But then he’d have answered the very simple question…what do you plan to do with this insight?
 
And he’d have replied;
 
“I’m going to target the customers who used to have the full suite of products but who dropped them 2-3 years ago. I figure with a little push and incentive I’ll be able to get them to renew those cancelled products.”
 
Interesting…so what Chad actually wants to do is to resell to clients whose spend reduced.
 
Don’t you scrape data on the financial position of all your clients over time? Doesn’t that data show that a good proportion of your clients revenue dropped 3 years ago? Could that be why they dropped some products? Oh…and look at this…half of those have returned to similar or higher levels of revenue in the last year. Chad should target them as a priority. Plus he might not even need to incentivise them too much, further increasing our profits.
 
So, why didn’t Chad ask for this data in the first place?
 
Because he might not even know it exists! How would he? You are the expert on data in your organisation while Chad is the expert on the best bars in the local area. We each have our specialisations.
 
Data consumers can only ask for what they know. When it comes to knowing what’s possible with data, they don’t know a lot. And even when they do, they definitely shouldn’t know more than you! You have to help them provide context in a systemised and consistent way so they ask the right questions.
 
Take this example. Chads initial question was simple. He needed some segmented sales data. You answered the question. It might or might not have helped. But by collecting further context upfront now the right question set expands. And with it, your chances of providing Chad with a successful project, as he defines it, increases.
Chad Toasting

Chad toasting the data team efforts in helping him get the best villa in Cabo. He just couldnt do it without you…

So make sure to actually forget the question that a data consumer asks you in the first place. You don’t know yet if its the right one. Collect context. What is it this person wants to do? What positive change is it they want to see, for the organisation, for their team…and for themselves?

The question asked is the most important thing. It defines how you build an insight, which delivers an outcome. Your data consumers are the most important team member. They most often deliver and live the outcome. And in data & insight, outcomes are everything.

Now you might be asking why do I need a system to collect such simple information, and it’s a good question. Luckily I have another blog post which answers it. The crux is that its bonkers to not use a system to collect your insight requests, because there is so much to gain.

I hope you liked this blog post. I think a lot about how to manage data & insight projects from the human perspective. Don’t get me wrong, I know how important tech is to Data and Insight. I just believe that the way in which people work together is key.

I managed data & insight projects and teams for 15 years, and got pretty good at it. But like everyone, I failed and messed up a lot. This gave me a fair idea of the simple things we can all do to increase our chances of success.

My startup, Brijj, is here to help.

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