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Outsource magazine: thought-leadership and outsourcing strategy | June 23, 2017

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Talking Analytics

Talking Analytics So What Now?
Outsource Magazine

This article originally appeared in Outsource magazine Issue #32 Summer 2013.

In April, Outsource teamed up with Wipro to host an afternoon of presentations and panels looking at analytics and information management. The event, which took place at Chelsea FC’s Stamford Bridge stadium in London and which was chaired by Outsource editor Jamie Liddell, was entitled “Leveraging Analytics and Big Data for driving operational efficiency and predictive asset management”, and attracted a broad range of professionals united by their interest in the dynamic big data and analytics arena.

The first presentation was given by Neil Chandler, Research Director at Gartner, whose session was entitled, simply enough, “The Future of Analytics & Big Data”. He began with some clarification around definitions – vital in such a rapidly evolving space – with terms such as “business intelligence”, “performance management” often being used by some organisations interchangeably with “analytics” to the confusion of many. Gartner, said Chandler, uses “business analytics” as an “umbrella term” to describe the full spectrum of this part of the space, and he offered the handy equation “Business Analytics – BI + Performance Management + Analytics” to lay any residual confusion to rest.

Whatever it’s called, Chandler made clear from the off that this is big business – and especially on the services side, with more being spent on service delivery than upon software: “If you look at things like the total cost of ownership of a technology over a five-year period, the initial purchase price of the software is less than ten per cent of the overall cost.”

Part of the reason for this, he explained, was the complexity of solutions in this space: “It’s not all around one type of decision support that we’re trying to deliver and it’s not all going to be delivered through one type of technology either.  There’s a vast array of different types of technology that we need to think about.”

Nevertheless, this complexity and the associated costs simply must be dealt with.  Chandler offered a stark warning to the attendees: “If your practice within your organisation today or the focal point of your business intelligence is still called BI and it’s still predicated on the data warehouse with some analysis or a BI platform, my task for you guys is to really transition to a business analytics space which encompasses BI analytics and performance management, and to plan something like a three-year roadmap of how you’re going to get from BI to business analytics, because for the IT people in the audience, it’s evolve or die! If you’re going to be just a gatekeeper at the data warehouse, then your role in supporting the organisation’ analytics strategy is going to be increasingly marginalised.”

From a financial point of view, too, tackling this issue can pay great benefits. Citing IBM research, Chandler explained that companies regarded as “transformed” in their embrace of analytics (as opposed to “aspirational” or “experienced”) had a 200 per cent revenue advantage over laggards in the study.

There was clearly some way still to go for at least a few or the organisations represented in the room, despite the aforementioned benefits, as only one attendee was able to claim that his company had a documented business intelligence strategy – something which Chandler said was of mixed benefits as “the first thing you need to do is to create a strategy for business intelligence, then you need to throw it away… because it’s going to be the wrong shape… We need to start from a business-centric value point of view and reengineer backwards.”

He continued: “Why do we do any of this stuff in the first place? Because the business has problems that technology can solve. That’s the only reason for doing it. There should be a good business case for analytics.”

Chandler closed his presentation with three takeaways for the delegates:  “Go and develop a business analytics team as a hybrid of IT and business people that are the foundation for this strategy.  Base it on the business analytics framework so it’s got ‘business analytics = BI + performance management + analytics’ as its strategy; and then develop the business analytics road map which is your 3 year vision for how that works.”

Following a very interactive Q&A session, the second speaker was introduced: Ajith Parlikad of Cambridge University, who looked at the topic of predictive asset management and asset data.

“To understand the real condition of assets, you can do manual inspections -or if technologies allow, you can use sensors to monitor continuously and then replace the asset before it actually fails… You need to have a whole life strategy for managing your asset.”

To do this, of course, requires data – and lots of it. Asset data includes maintenance information, location data, compliance data and financial data, and all of this needs to be obtained, stored and analysed. And here, Parlikad said, “the key to effective data management is embedding a data-driven organisation culture.”

Echoing Chandler’s comments earlier, Parlikad closed with a useful mantra: “Data analytics is useful only when you are using it to drive decisions… There’s no point in doing all sorts of fancy analytics and not using it actually to do things better.”

Following this presentation the delegates moved to an intra-table discussion session looking at their own places on the analytics maturity curve, which threw up plenty of fascinating insights. The importance of embedding a data-focussed culture highlighted by Parlikad was endorsed by several of the groups, as were Chandler’s points about the value of a coherent business case and of using the correct definitions to avoid confusion. One interesting takeaway was that many organisations still suffer from a clash between the desire of the business for robust reporting information and the interests of the analytics teams in using data more profoundly and transformatively (but not being allowed the resources to do so). This appeared to be exacerbated by the silo effect, with different parts of the business failing to work together to produce a concerted analytics “wishlist”.

Following this phase, the delegates were brought back together for a panel debate featuring some big buy-side names looking at their own experiences with analytics and the challenges they’re facing; the event was then rounded off by a stadium tour and a humorous Q&A with a Chelsea FC legend (bringing a degree of light – if frequently scurrilous – relief to proceedings). After dinner, the delegates went home full of both food and extremely useful takeaways about how – and why – to drive the usage of analytics through their organisations.

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