6 steps towards smarter data — where do you even start?
The business that can get smart about data is the business that will go further in the digital age of business. We see it every day with our clients, who are using the insights of data to either radically redefine their business models or make improvements in operations, quality, and service. Whether you’re looking to cut costs or keep up with disruption in your industry, the more intelligence you have the smarter your decisions will be.
For Dimension Data, the Tour de France in 2015 proved to be a great data analytics story. It got me thinking about the best way business today can start — or rethink— their own journey towards big data.
Step 1: Define the outcomes you’re looking for
There’s a tendency to complicate analytics, with a belief that you won’t know what you’re looking until you get your hands on a large set of abstract data. This isn’t necessarily true. In many cases, you absolutely do know what you’re looking for at the start. These can be simple needs but they need to be clearly define.
For example, in the Tour de France, it all started with the rider. We needed to know the position and performance of each rider during the race. But in a manufacturing plant, you might need to assess quality control, or how a machine is performing and when to schedule maintenance. In an insurance company, you might want to discover the source of claims irregularities or outright fraud.
Step 2: Decide how you’re going to capture data
While your objectives may be simple, often you don’t know how you’re going to collect data and make it consumable in the shortest space of time. For the Tour, we had to have real-time data analytics — it would be pretty boring to get a day or two after a race stage.
Our technical team had to create a mesh network that would relay data from gateways in the race to an aircraft overhead and then to the technical zone set up at the finish of each stage so it could be fed to broadcasters and social media platforms. In short, you have to think of the most logical framework or infrastructure in order to support your big data ambitions.
Step 3: Adapt the solution to fit your unique business model
When you’re tracking some of the world’s top cyclists across the French countryside and atop mountains, you can’t always depend on the kind of Internet reception or connectivity you’d find in a business park or urban area. That’s what made our solution for the Tour challenging (and also exciting!)
It’s critical that your infrastructure must fit your business and delivery model and not the other way around. For many companies — especially those entering the digital space — it’s better to get some advice on the best infrastructure investments to match desire business outcomes.
Step 4: Discover how to leverage agile data to make faster business decisions
The Tour de France is a race where things can change in a heartbeat. For viewers, these dramatic shifts in the competition is what makes the race so exhilarating. The data we fed to the race organiser A.S.O.’s broadcaster partners in 2015 allowed never-before-seen live-speed data. Our beta live-tracking site, coupled to live data updates on social media, changed the way fans consumed the race … from day one!
We knew we’d need reliability, scalability, and flexibility on our platforms and be able to evolve and refine our solution as we went along. In your business, it’s equally important that your model allows you context to make immediate business decision-making value.
Step 5: Evaluate data to identify patterns and discover new insights
While the data you’re running can provide real-time decision-making capability, it can also give you a rear-view sight of things you may have missed — and start looking at patterns you hadn’t even thought of the first time round. So … where do you keep it?
For the Tour, our cloud platform proved to be the bedrock of our solution. For your business, you might want to keep those massive volumes of data in a public cloud before you decide what you want to do with it and then, later, move the more sensitive data to your own data centre or private cloud.
Step 6: Segment and prioritise data tiers to share with relevant users
The Tour de France has a staggering cumulative TV audience of over 3.5m viewers across the world. However, different broadcasters had signed up for different amounts and types of data so we had to segment our delivery model between them, as well as provide data for the tracking website and social media.
This is the probably the last, but most important, step in your big data journey. Once the data has been cleaned up and analysed, you have to decide who you need share it with to get the most value out of it.
The truth is you’ll probably need different types of critical data at different times in your business cycle — but you might not want to share it with certain stakeholders, like your clients, until it’s been analysed. So it’s important to create different tiers of data that offer different levels of insight. How you structure these tiers and share them is as important as collecting and storing the data.
Broaden your data pool
Once you start analysing your data, you’ll harness the power of smart data to improve your business and sharpen its competitive edge. You might start asking, ‘Yes, but what if I also had this type of information?’
At the end of the day, you’ll have to justify your investment in infrastructure, resources, and other analytics tools. The more insight you can extract and exploit from your data, the more tangible business value it will create which will, of course, justify more investment. The best advice: start simple, but start the smart way.