How to ensure advanced analytics gives you a concrete competitive advantage

Most companies these days are aware of the potential value that advanced analytics could offer them. Lots of people are talking the talk of advanced analytics, hiring data scientists and investing in sophisticated analytics technologies. But these things on their own aren’t going to give you the competitive advantage that you’re hoping for. It’s not possible to bolt advanced analytics as an adjunct to your marketing or strategy function and hope that the magic will happen just like that.

We regularly talk to people who’ve invested a lot of money in advanced analytics software and are wondering why they’re not seeing the value on their bottom line. People who’ve invested enthusiastically in new analytics tools and then are disappointed to find that they’re not really being used. Why does this happen and how can you avoid it? To reap the benefits of advanced analytics it needs to be properly embedded throughout your organisation. So what does that look like in practice?

Training that’s user-focused rather than application-focused

If you’re investing in advanced analytics software, then it makes sense to also invest in some training to make sure everyone in the team has the skills they need to be able to use the software. It can be tempting just to send everyone on a standard off-the-peg public training course, the basic one day ‘introduction to…’ format.

Doing that is of course better than nothing, but the limitation of such courses is that they’re not tailored at all to your specific requirements. Everyone gets the same experience, learns the same software functions and gets to play with the same dataset. Included in that will probably be some stuff that your team find useful, but they might have to search for that in amongst a load of stuff that’s not directly relevant to them.

What’s much more valuable is to invest in some tailored training that’s specific to the requirements of your organisation and your team. The trainer takes the time to understand your particular objectives alongside finding out more about what kind of analytics you’re doing, what sort of data you’ll have access to, the skills and experience of your analytics team, and then builds a training course that concentrates on those areas that you’ll find most valuable.

People often worry that this kind of training is going to be much more expensive that standard public training courses but the reality is that if training doesn’t get people actually using the software then it doesn’t matter how cheap it was – you wasted your money. In fact, for a very similar price you can get a fully tailored training course, delivered onsite to your team, with training exercises and materials developed using your own data (find out more about the bespoke training that we offer).

Analytics must be driven by the needs of the business

It’s not unusual to find that ‘the analytics’ is done by a team of analysts or data scientists who work almost separately from the rest of the organisation, but to get real value from your analytics you need to make sure that it’s driven by real business needs, and for that to happen it’s vital that business users are involved in the analytics conversation right from the start.

Data scientists are often people who are fascinated by the data and the process of analytics. They’re happy to spend time digging about in the data looking to see what they can see. This exploratory urge needs to be harnessed and focused on the organisation’s specific objectives.

Business users might not have the analytics skills of the data science team but they’ll probably have a much deeper understanding of the realities of the business, of the context in which it operates, and of its strategic requirements. When advanced analytics really adds value, it tends to be in situations where the analysts and the business users work together in a close partnership.

Build analytics into your workflows and decision processes

As I’ve already discussed, analytics works best when it’s embedded throughout the organisation rather than treated as a separate function. Think about how you can embed your analytics into your daily workflows and operational decision making processes. Invest time in developing as many automated processes as you can so that the analytics can run in the background, informing the way in which people do their jobs on a daily basis. You’re aiming for the integration of advanced analytics to be part of standard operating procedure rather than a separate process.

Push your successes and make sure people know about them

You might find that you’re up against sceptics in your organisation who don’t understand the value of analytics, or are in the habit of making key strategic decisions based on gut feel rather than on data. I’ve spoken to lots of business owners and senior managers who have always adopted this approach and can be very sceptical about the value that advanced analytics might bring.

The best way to manage this is to be proactive about measuring the success of your analytics projects and making sure that everyone knows about these. Business owners are generally very motivated by anything that can help them improve business efficiency, save time, work smarter and, ultimately, make more money. In my experience even the most sceptical managers tend to come round to the idea of embedding advanced analytics in the organisation once they see concrete examples of the value that it brings.

Be realistic about what’s possible

Quite often we come across organisations who are effectively paralysed by trying to do too much. Once you start thinking about all the sources of data that you have and all the questions that you might want to answer, advanced analytics offers almost unlimited possibilities. It’s easy to spend all your time on this stage of the project, thinking about what you could do doing rather that actually doing something.

Much better is to be pragmatic and start small – don’t try and boil the ocean. Think about what might constitute a quick win and make a start on that project. It’s much easier to convince others of the value of advanced analytics if you’ve actually got a couple of discrete projects on the go that people can easily get their heads around, rather than trying to persuade people on the basis of the infinite variety of possible outcomes that there could be.