In the modern data-driven economy in which businesses now operate, the ability to gain insight from data is critical to a company’s ability to survive and thrive. Whether that data comes from real-time sensors from an IoT environment, or a big data platform with massive amounts of disparate data, the ability to connect to and analyze information is paramount. In other words, analytics is no longer a nice-to-have capability. It’s something companies must have – and must have now. With that in mind, here are five best practices organizations of any size can leverage to get started with analytics.
1. Start with a specific business question
Though it may be powered by technology, analytics is, at its core, a business trend. That’s why any organization looking to get started with an analytics initiative should do so by outlining a specific business question. The word “specific” is critical here. One of the more commons mistakes even experienced companies make with analytics is starting with a goal that’s either too broad or not clearly defined. The goal of an analytics project can’t just be to find new customers or create more revenue. You have to get more specific. So, instead of looking at how it can increase revenue, a financial institution might look at how it can reduce the occurrence of fraudulent credit card applications from customers in New York City. Or, instead of looking at how it can produce more drugs, a pharmaceutical company might look at how it can reduce the occurrence of lost batches at its manufacturing facility in London.
Whatever the case may be, the more focused the starting point, the better. Having a clearly delineated objective not only ensures that everyone involved knows what you’re trying to accomplish and how you’re trying to accomplish it, but it also makes it far easier to build support for the work across the organization.
2. Secure executive support
Speaking of building support across the organization, a critical early step in any analytics initiative is to secure the buy-in of company leadership. That’s why outlining a specific focus is so important, because the ability to clearly summarize what you’d like to do, and how it will directly benefit the business, will go a long way toward ensuring you get the right level or organizational support and investment. That support and investment goes beyond just the funding of the effort.
The purpose of an analytics project is to drive change by uncovering insights from data. The analytics can do the latter, but it generally takes company leadership to do the former. After all, the insights gleaned from analytics are only as useful as the willingness of those in charge to act on them. If leadership isn’t (or never really was) willing to take action, then your project was fated to be a novelty project – one limited to producing interesting, but useless information – before it even started. So, after outlining a specific business question, but before officially kicking off the project, put in the work to evangelize and secure the support of your company executives, such that by the time the project kicks off, they’re just as (or more) excited about it as you are.
3. If it ain’t broke, still fix it
Perhaps the single biggest misconception about analytics is that it must be applied to either fix something that’s completely broken, or discover something that’s completely new. Now, can companies occasionally achieve those types of outcomes with analytics? Of course. But it’s important to remember that those instances are the exception, not the norm, and if that’s where you’re starting with analytics – with a mission to fix something that’s completely broken – you’re going to have your hands full.
The better way to leverage analytics and get the most immediate return on investment is by using it to augment or enhance a process that already working. Take a NASCAR pit crew for example. Clearly, these are folks who know a thing or two about getting a car into and out of pit row as quickly as possible. That’s by no means a process that’s broken or needs fixing. But what if a race team could get their driver back onto the track half a second faster – an eternity in racing – by using analytics to account for the impact of wind speed and direction on the efficiency of the pit crew? You better believe that’s an improvement they’d be eager to make. That’s just one example, of course, but the takeaway applies across all industries and vertical use cases. Identify something you already do well, and leverage analytics to do it even better.
4. Leverage the community
It’s no secret that there’s a shortage of data scientists. They’re hard to find, and hard to afford when you do find them. And even when you do find them, and can afford them, you’ll still never feel like you have enough of them. So, yes, there’s certainly a skills gap. But it’s by no means one that can’t be overcome, especially if you make addressing it a priority right out of the gate. First and foremost, organizations should seek out the analytics platforms that do the best job at abstracting complexity and simplifying processes for both technical and non-technical users. That alone will go a long way.
So too will leveraging the concept of collective intelligence. There’s a growing movement among experts in the analytics community to share analytical models with a broader audience via online marketplaces. In other words, they build it, you license and use it. That means organizations lacking the skills to build the right analytical models themselves can now leverage the work of those who do have the necessary skills – all without having to hire those experts directly. There are a small but growing number of vendors in the marketplace focused on delivering this collective intelligence to end users. Any organization getting off the ground with an analytics initiative for the first time would be wise to consider tapping into the collective intelligence of the broader community.
5. Set expectations and stay patient
As with any business initiative, setting expectations is critical. And not just with company leadership, but with yourself as well. Transforming the culture and capabilities of your business isn’t something that happens overnight. It’s not uncommon for it to take between 6 and 12 months to truly reap the rewards of a well-run analytics initiative. That might seem light a long time, but remember, analytics is an investment in improving your business for long-term by creating competitive advantage and increasing your portfolio of defensible intellectual property. Focus on the right business questions and approach it the right way, and that patience and investment will pay off and then some.