It’s the shoemaker’s son conundrum: I have always found it ironic that insurers, whose whole business is based on the management of information, have struggled so much in understanding and utilizing the information they have. Could one question give the child some decent shoes?
I have listened to insurers for over 20 years talk about the need to report more accurately, provide management with more business insight, manage fraud more proactively, price products more effectively and understand customer needs, wants and behavior, and I can walk through many examples of failed projects trying to address these domains. Global insurance executive surveys over the last couple years show insurers recognize that they need greater strength in management of information to handle increasing regulatory pressures, improved customer service and insight, increased outside collaboration and overall operational effectiveness. So with all this business pressure and pent up demand, why are these problems so difficult to solve?
What the problem is not …. And is …
The problem is not universal. One can see global examples of insurers making great advances in analytics and use of information, but these examples hardly represent the norm (certainly not in Canada). And the problem is not related to scale. One doesn’t need to be a large firm like Progressive Insurance to use data insights to price more creatively and profitably.
Certainly there are many obstacles to overcome, both within I/T management and control and in the business. There are data quality and consistency issues in most carriers, at least until carriers focus on much improved intake processes. There are data ownership and governance problems to solve (e.g. have you established business “ownership” for all data within your enterprise?).
There are probably some skills issues to solve if an insurer wants to embrace analytics throughout the enterprise, but skills shouldn’t be a short term issue. Luckily, there is no shortage of tools on the market and arguably the current generation analytical and reporting tools do overcome some of the historical technology challenges in extraction and cleansing. So is the issue more with the definition of the business problem and related business case for investment to solve it?
I believe that there is a direct correlation between scope of projects and risk of failure. The breadth of scope is not actually the issue but with greater scope often comes lack of clarity of business requirements and key business drivers. What I have seen too often is an attempt by IT to solve all analytical problems through one solution, rather than forcing a better definition of the problem to be solved.
So here’s The Question ….
I was speaking recently to a Canadian COO who was frustrated with IT’s inability to deliver a “business analytics” solution in a timely fashion. I asked “but what ONE business problem specifically are you trying to solve?” The answer was that the firm needed much better insight on product pricing. I then asked “and what you would you estimate the hard dollar benefits to be if you could get the answers you are looking for?” That answer was harder to come up in specifics, but we agreed on a reasonable number.
Very quickly we determined how much the business could afford to spend on an IT solution and that organization could quickly assess their own capabilities and feasibility of fitting within that budget. So, by discussing the end result or “the question that needs to be answered”, we could then narrow down the specific business scope, a potential business case around sensible investment, a set of actions to determine data sources and some potential actions by IT to deliver the required data.
It might not be silver, but it is a bullet, and there is a target …
By no means am I suggesting that every insurer should go out and try and get 100 questions answered with 100 independent business analytics projects. A more holistic approach to establish a reusable platform to deliver reporting and insights to the business is naturally what each IT organization should strive for. Skills and organization to support broader analytics based solutions should be considered. But narrow, targeted and delivered (in the short term) analytical solutions that provide both business benefits and IT learnings are far better than inaction. And remember, if each project is business cased, what is the downside?
So what do you think?
Do these problems have a ring of truth with you? Have you been able to break the cycle with an approach like this? Leave your thoughts below.
Editor’s Note: David Kerr ([email protected]) is Managing Director, Insurance Practice, Accenture Canada. He has 26 years experience in providing value-added advice and solutions delivery leadership and has worked almost exclusively with the insurance industry for the past 22 years.