Pradeep Menon, Global Analytics Head, Maersk GSC
A few weeks ago I met up with my colleague who heads our conglomerate's internal consulting division. It was a long planned meeting between the leaders of the analytics and consulting divisions to catch up and as these things sometimes go, finally came to fruition a few months behind schedule but with a sense of real urgency this time. The urgency stemmed from the fact that there were a couple of key strategic initiatives spawned in some of our group business units that we realized we could not deliver on till we joined forces. It was difficult to provide a holistic solution to the problem, working in our silos.
And such is the dynamic at work amongst the in-house analytics and consulting divisions in almost all captives today. Gone are the days when one could take on a process redesign or a market mapping assignment and deliver all of it effectively by legging it all alone. Utilizing the synergies between those who advise and those who analyse is paramount to ensure that projects are delivered on time and in line with the needs of the project
The field of decision sciences and analytics has been gathering momentum in the past couple of decades and its only growing stronger with each passing year. Organizations are increasingly realizing the sheer insight potential that the data in their process systems and data warehouses hold. Every attempt is being made to eke out that last bit of intelligence from databases which will help companies make a ‘better’ business decision which will eventually help them win quicker. Technology options and architecture choices abound when it comes to designing the 'thinking organization' of tomorrow.
It’s an all pervasive change across industries. Some lag the others when it comes to the depth in which analytics has penetrated their business processes today. Traditionally something used by the finance and e-com industries to segment and offer differentiated products to their customers, today analytics has spread its roots into pretty much all walks of life. Even older-age sectors such as mining, shipping and the energy sectors have woken up to the potential that it has to transform their marketplaces.
Initially analytics offerings revolved primarily around providing management information support, mainly dashboards and reports that kept organizations running. It evolved later to use more of visualization tools as time went by, focussing more on identifying why and when things were going wrong and what the right response strategies should be. The ability to analyse various what-if scenarios came up and decision sciences as a field started evolving to meet the needs of the functional decisions that needed to be made. Advancements in machine learning algorithms and the topological exploration of big data sets have brought out the ability to process vast data stores intelligently to such an extent that it’s reached a point wherein one can link static information to neural networks that can think and mimic human decision making. An 'e-manager', in fact seems like a distant ‘reality’ now given the rate of advancement in this field.
Success though is not always a certainty. A lot of analytical projects in organizations fail. Not necessarily because of skill gaps but many a times due to not understanding the exact context behind the problem being analysed or not having access to the right data sets. One way in which, mature analytical setups deal with this is to build-up a good insight into the data maps and information flows in their respective companies. That goes a long way in identifying the right data sets to target while working on a problem. Having analysts work closely with business or consulting partners is also very important in building context to the problem being attacked. It has a huge bearing on the relevance of the analysis carried out. Partnering with colleagues in the consulting space and working on joint projects goes a long way in building context and depth too.
As internal functional divisions increasingly become aware of the potential value they can unlock using their analytics colleagues, it’s also equally important for analytics divisions to ensure that they partner well with all departments in understanding their pain points. It’s important for analytics ‘partners’ to be integrated into the teams they support. They need to be a part of all key business meetings and be present in all important forums so that they are aware of all the key imperatives faced by the teams they support.
The meeting I referred to earlier in the article was all about inking these details out for a strong future collaboration between our consulting and analytics divisions. With strong leadership connect and sponsorship, this will go a long way in providing strong sustainable competitive advantage that we can leverage.