What Makes A Successful Data and Analytics Project?

“Gartner predicts 2017 will see 60 percent of data projects fail.”

That’s not as shocking as it sounds, mainly due to my experience in what happened with both ERP and CRM when they were introduced in the world of business, and I think companies still struggle with those too!  Mind you I don’t know what the real numbers are, and I’m expecting them to be worse!

As data grows at an astonishingly ridiculous rate the IDC predicts “the digital universe is expected to reach 40,000 exabytes by 2020.” Exabyte = 1 000 000 000 000 000 000 Bytes!  I can’t quantify that!  I’m sure there is someone that can tell us how many football stadiums that amount of data can fill!

Moving on from that I’m not going to talk about the failures today, because, I would prefer to highlight what makes a successful data and analytics project.  If this amount of data is coming at you, then you need to understand how to create successful projects and gain value from your data.

The Top 6 Success Factors

1. Organisations that have a clear data and analytics strategy with an end goal in mind, benefit most from data and analytics projects. There are many new shiny things on the horizon such as Artificial Intelligence (AI), Machine Learning (these two aren’t really new), The Internet of Things and Cloud is obviously growing at a pace, so getting the strategy right will allow you to make the right decisions for your business and its future. Don’t start with an AI project because it’s still in it’s infancy.  Get the basics right that will help you move towards the really cool stuff!
2. Crafting the strategy will help you define several business challenges / opportunities that offer huge quantified benefit to the organisation. These could be improving operational matters, or going to market quicker with a product or generating more revenue in a specific customer segment.
3. Identify the right senior level executives to gain buy-in and will help move things forward. It’s the usual aspect here, there are many people in organisations that don’t like change, bring those people into the fold early, do the education up front about the importance and the benefits that will be achieved.  When the project ramps up, bring them into key decisions, understand their needs, show them prototypes that are being built, get their feedback until they see how it will help them and their line of business areas.  Change management isn’t something to be balked at in this case, many a project have been derailed because of the sceptics, don’t let that happen in yours.
4. Ensure you know what you will do with all your data. Once you have your requirements, map these to the data that you need.  What will emerge are three buckets that will support the success of your project: 1) Which data is available now to meet some of your requirements, 2) which data will be available in say 3 months as it is part of a new system roll-out, and 3) data that will need to be acquired to enrich your current data to meet your requirements.  Doing it this way will help you see the roadmap and priorities, therefore, not working on stuff that isn’t going to make a difference yet!
5. Make sure you get the right skills sets that you need for the project. Don’t just go out to the market and think that you need to hire data scientists, due to it being the latest job title that is the only one being talked about.  You will need an array of people on the project: business analysts, data analysts, data engineers, BI developers / analysts etc.  Don’t be lured into the latest fad and realise you don’t have the right people to make the project a success!
6. Lastly, I will talk about technology. Don’t whatever you do, go out and buy the tech before you know what you are doing, why you are doing it, who is going to benefit, when it can be done and where within the business will have the biggest bang for your buck! I know it sounds very simple, but, believe me there are many organisations that go out and buy tech, and then fit it into their business.  Don’t be one of them.

Companies today hold a lot of data which is complex and in a labyrinth of systems.  It simply won’t help sending your existing staff on a short technical to get the benefits from your data.  Make sure you bring in people that have done this time and time again.  Otherwise as a wise man once said:

“Insanity Is Doing the Same Thing Over and Over Again and Expecting Different Results”. Albert Einstein