JJJinu Johnson: The one golden rule that I practice and often preach to others is to avoid ‘analysis paralysis’. The biggest strength of most analytics division tends to be their biggest weakness as well. Most analytics divisions are renowned for their attention to detail however if constant reviews and permutations result in delay, then you have not empowered the powers that be with the relevant tools for effective decision making. My policy has always been to ensure that decision-making is facilitated through timely business intelligence and to avoid ‘analysis paralysis’.
AIM: What are a few things that organizations should be doing with their analytics units that most don’t do today?
JJ: Whilst analytics units continues to be the centre of excellence on data and information, one often overlooked facet is that to be this centre of excellence, there needs to be great synergies with the IT division and as such decision science specialists tend to have good knowledge of IT architecture as well. Organizations need to start leveraging these skillsets of analytics units; not just for decision science but also for other critical IT projects as well, particularly because the Analytics units tend to have both business and IT acumen.
AIM: What are a few things that Analytics units should be doing differently that most don’t do today?
JJ: Analytics units tend to be more business intelligence focused as opposed to analytics focused. The core focus on data production takes centre stage that interpretation often remains wanting. The analytics units need not remain the custodian of data but rather use the information and develop business strategies, challenge the status quo, drive business growth- be instrumental to business growth and not just incidental to it.
AIM: What are the most significant challenges you face being in the forefront of analytics space?
JJ: The rule of thumb in data analytics is that ‘junk in’ then ‘junk out’ – if data integrity is suspect then any output derived from it would be redundant. Data quality, legacy information architecture and disparate data sources continue to plague most organizations and these are the major bottlenecks. However of late there is a general recognition of these inherent flaws and holistic approaches are taking place at an enterprise level, which should soon reduce the challenges that we face today. However the capital outlay that is required to invest is more often the deciding factor.
AIM: How did you start your career in analytics?
JJ: I started my banking career in branch banking with a major bank in India, thereafter moved to the GCC region for a regional bank as an analyst and later on managing the analytics function for the bank. Currently am heading the analytics function for a top tier MNC bank and presently am based out of North Africa. The front line experience coupled with support function experience has been a game changer for me; it helps to put things in perspective and particularly so when dimensioning data.
AIM: What do you suggest to new graduates aspiring to get into analytics space?
JJ: I have only one suggestion – “Pay your dues”. Yes, everyone would love to start as a manager or senior associate leading people, but if you wish to grow in this industry, start at the very bottom. Roll up your sleeves; the devil is in the details. Be detail oriented in your initial stages of your career, pay your dues so that later on when you see data at a helicopter level, you are able to relate.
AIM: What kind of knowledge worker do you recruit and what is the selection methodology? What skill sets do you look at while recruiting in analytics?
JJ: Depends on the seniority. For junior roles, its best to recruit for attitude and train for skill. For mid to senior roles, attitude and aptitude is key, additionally the business acumen and past experience plays a pivotal role. But the one over-riding barometer that I use to measure quality of selection is attitude.
AIM: How do you see Analytics evolving today in the industry as a whole? What are the most important contemporary trends that you see emerging in the Analytics space across the globe?
JJ: I see a few paradigm shifts taking place. Without a doubt the influence of cloud computing and acceptance of Big Data are the front-runners. Piggy backing on cloud computing is ‘SaaS’ – Software as a service. In the banking domain there is a shift to mobile and tablet technology, soon analytics offerings will need to be tablet optimized for easy read by executives whilst away from desk.
AIM: Anything else you wish to add?
JJ: Always remember that the packaging is as important as the product, cosmetic surgery is key. Pictures speak louder than words. As much as possible stick to the policy –“less is more”, package your data output in such a manner that its simple to understand and ready for consumption. You may have breakthrough information but if its not presented well, there will be no uptake.