Video TranscriptHello everybody, welcome back to This Not That, where we talk about best practices in the data and analytics world and compare them with some really common mistakes that we see in the industry. Today we’re going to be talking about the business process. How you think about that when you’re working on a data project and the ROI that you’ll get out of it.
Welcome back everybody!
So, one of the things that I commonly do as a consultant is I go into client meetings and we have a conversation: Where is your company at? What sort of things are you dealing with? Etc. And what inevitably happens at the end of this - and it’s a good thing - is we get to the questions: well what is it that you’d like? What is the end goal for you?
When you ask that ‘what’ question, what THING do you want? I found often people are trapped by the tools that they’re familiar with. So, to the person who has a hammer, everything is a nail as the old saying goes. I find that true for me as well. I think about the skills that I’ve got and I’ll approach a problem, and immediately try and slot that problem and it’s solution into the tool sets that I have.
There is a good way to get around this, and that is to focus on WHY NOT WHAT. What do I mean by that?
Once you start asking, why do you want this thing? Why do you want this report? Why do you want this database? Why do you want this machine learning algorithm? Once you ask that why, and often follow it up with another why, it can get a bit annoying. But go down this series of ‘whys’. Why this? Ok, I understand that now. Why that? Ok, I understand that now. And just keep working backwards until you’ve hit something solid and concrete that directly impacts the business.
When you know that ‘why’, now you can open it up to all kinds of tools that might be a better solution for what it is that you need to accomplish.
So, some real-life examples: I spend a lot of time building reports, that’s the majority of my job. When I go to business users to ask them what it is that they want, usually they’ll say ‘well, here’s my job, here’s what I do. I need these 75 data points preferably as raw data.’ This is a common thing that I run into.
If I start asking them why they need that: ‘Ok what decision are you going to actually make? If I give you this data and let’s say it’s all bad, then what do you do? Let’s say it’s all good, what do you do then? Why? What are you going to do with all of this information?’ That question sparks a new kind of convo and out of that can come something really useful.
I have a reporting skillset. Sometimes that’s not the right answer for the why. Sometimes I’m not the person that you actually want to talk to. Maybe what you really need is to figure out when this ‘thing’ goes wrong, I want this automatic process to occur. I don’t want a report, I don’t want analytics necessarily, I want an automated action to happen. If this thing is unprofitable, I want this thing to occur as a result of it.
That sort of step back to ‘the why’, the real biz scenario, will point you in the direction of the right tools.
So my guideline: try and get to why and don’t get stuck on what.
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Hope you guy shave a great week and I will see you next time!