Big Data 101 - Part Deux

Picking the right problem

Big Data 101 - Part Deux

Picking the right problem?

You’ve got so many data problems that need solving, how could you get this wrong? Surprisingly it’s very easy and often terminal. It’s important to get this right, so what are the key things to consider?

  1. The problem must have business value
  2. It must be achievable with your skills
  3. It must be achievable in a reasonable timeframe

When it comes down to it, if you can put a tick in the box for each of those for your identified project, then you’re on the path to success.

But wait, surely there must be more to it, I mean this is Big Data right? Actually, I’ll let you in on a little secret. It really can be that simple as long as you’re strong, stick to these principles and have a good handle on what’s possible. Let’s drill down in a little more detail to explain the approach.

Firstly, business value, what do I mean? Well it’s critical that you pick a problem that has real and tangible value to the business. When I say the business I mean business people, yep those guys with the money who look at you blankly when you mention ip routing and dns addresses. One of the biggest risks I see in Big Data projects is technical people selecting cool technical problems, because who doesn’t like a cool technical problem? Answer: the guys with the money. So don’t be that kind of technical team, work with business people to identify some valuable business problems that could be solved with this technology and approach. The critical point is this. It’s very important to bring knowledge of new technologies and techniques to the business table, no one else can do that, just make sure you use that expertise to solve a real and pressing problem for the business people who are funding the initiative. To do that you need an equally good understanding of the business process and the technology sides of the problem.

After you’ve got a shopping list of real problems you need to take a good hard look in the mirror and decide which you have the skills to undertake. Optimists beware, you’ll get your fingers burnt here, so make sure you’re honest and pragmatic. What can you do now? Can you fund external help? Remember as I explained in part 1 of this series, learning is an iterative journey, early success will build confidence for more ambitious projects later. The same can’t be said for the opposite approach.

Project scope, this final part of the process is where a lot of projects come unstuck. Why? Well everyone wants a big cake with all the extra’s for their birthday don’t they? It is very natural for expectations to be high and for many different business groups to have long lists of requirements. If left unchecked, they will put you in the middle of the ocean, tell you to boil it, then watch you drown. This is where you need a good leader for your initiative, who can communicate and set clear expectations (this is what I meant when I said you have to be strong). It’s not that people want to drown you in the ocean, they just don’t realise they’re doing it. So tell them clearly that won’t work and educate them on what success can look like. They will thank you at the end even if they grumble at the start. Some of you more detailed people might wonder what I mean by a “reasonable amount of time”? That often depends on the organisation. My experience is that if you can’t show value within 2 months, make the problem smaller. If you don’t they’ll forget what you’re doing and you’ll lose all the support and momentum you worked so hard to build.

By following these 3 simple steps you will intimately understand what realistically can be done to start and continue your Big Data journey.  What’s more, all of the other stakeholders involved in the project will understand as well. When everyone’s pulling in the same direction it creates a very exciting and powerful energy. Harness it and you will make progress in leaps and bounds.

In my next article I’ll be talking about the final piece of the puzzle, selling your idea to the business and senior staff (yep those pesky guys with the money again). It’s the final hurdle so your daren’t fall here.

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