Buying the analytics platform was the easy bit – now how do I use it?

If we were to believe the hype, peddled both within the media and by technology vendors, turning big data into enormous business benefit is simply a matter of writing a cheque and buying the latest, greatest analytics platform.

I spend a lot of my time talking with senior people in industry, particularly with R&D leaders. The topic of Big Data and Analytics keeps coming up, time after time.

Now, it’s not in question that many of these platforms are fantastic bits of kit, capable of doing great things. So I ask myself why am I collecting an increasing catalogue of bitter and expensive tales of technology implementations that have failed to deliver the intended value?

The conclusion I have reached is that this is not a technology issue. It is a people issue. The constraining factor is not the capability of the analytics platforms – I think the technology is there. Rather, it is the ability to find the right people, and put them into the right organisational structures needed to turn the technology’s potential into actual value and benefits.

This goes far beyond the implementation of some next generation IT. A successful analytics organisation has to be able to deal with a different set of challenges than those we are familiar with in the rest of our business. While the heartbeat of a typical IT implementation project might be measured in weeks or months, the analytics team may only have a window of days, hours or even less, to provide insight and answers in time to influence a decision. This places great demands upon an organisation to be agile, flexible and capable of moving at great speed.

The breadth of skillsets required is typically much wider than we are used to in other functions. If we are to have the right tools for the job, across the breadth of questions that can be posed by the business, we may need skills in fields as diverse as text analytics, advanced statistics, modelling and simulation, data visualisation, and many more. Not to mention the new ones coming on stream all the time. We also need those skills to be possessed by staff who can work across the boundaries of IT and data sciences, as well as having knowledge of our business domain which, in many R&D environments is a scientific specialism in itself.

Even if we could find enough of these rare beasts, the range of skills that we need to be able to access is wider than we can practically, or economically, maintain in a full time team. And you never know what is around the next corner, as a new part of the business uncovers the next analytics challenge.


Experience is showing that our existing approaches can no longer keep up. Can we really find an outsource supplier, define clear project deliverables, get a contract in place, have the work done, and get the results back in house, understood and presented to the head of R&D in time for his meeting in a week and a half’s time? According to the industry leaders I talk to – no chance.

Before this starts to look like an insoluble problem, let’s think again.
For organisations who expect this to be a recurring issue, the answer may be an Analytics Partnership. If built correctly, a partnership will deliver both continuity and flexibility. A good partner should work closely with you to understand the flow of analytics challenges coming along, and help profile matching analytics skills and bandwidth requirements. They will combine that with a flexible pool of technical specialists to cover the breadth of your needs and have the necessary service agility to supply them at the right time.

For the partner, delivering analytics across multiple clients, in multiple industries, allows demand to be balanced, and a larger, more flexible team to be supported. The client base meanwhile gains from the cross fertilisation of ideas that results from multi-industry experience. Think how often you wish you had the opportunity to lift your eyes up from today’s issues and see how your peers in a completely different industry had already solved an analogous problem?

Your analytics technology platforms can be significant investments. But it’s the data that they collect, manage and process that are your real assets – so you have to start thinking about data as if it were every other asset you own of great value. Maximising the return on investment in that asset will need the development of new structures and capabilities in your own business. But it also requires looking outside – not just to the rest of your industry, but also to other industries, and to partner organisations. Your new data assets will then be in the right mix of hands, bringing together crucial domain knowledge and specialist analytics. Achieve that, and then you’ll really get to see what your analytics platforms can deliver.

Alan Bell

Alan Bell

Dr Alan Bell is Sector Director for Life Sciences and Healthcare at Tessella. For the last 12 ...

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