The Top 3 Errors of Analytics and How to Prevent Them

By TMCnet Special Guest
Etienne Castonguay

An Analytics program of even modest proportions is always a big undertaking. Aims and goals must be conceptualized and formalized. Teams must be put together. Milestones must be established and schedules devised. But even with the best intentions, it’s all too easy to fall unwittingly into some traps — traps specific to the Analytics world. Not only can early missteps delay production, but they can also end up wasting effort and costing major dollars. However, with awareness, the most common mistakes can be identified and avoided, before they become entrenched in the plans.

In this article, we identify the common traps to avoid and then we conclude by proposing four key steps to help you evaluate the validity and strength of a proposed Analytics roadmap. We are confident that with this approach you will be able to have a much clearer strategic vision of your Analytics initiatives, better understand how it fits in current and future states of your industry.

Bring the right people in from the onset

More often than not, Analytics programs are initiated, developed and even “owned” by experts in Information Technology. This “build it and they will come” approach has strong appeal, and on the face of it appears sound. But an Analytics program that is not regarded, first and foremost, as a business challenge will quickly become misaligned with corporate strategies and business interests.

To avoid misalignment, bring in the business angle from day one.

?Bring executive support from the start

A lack of executive sponsorship weighs heavily on an Analytics program. When no senior executive is clearly identified as a stakeholder, different visions can compete against one another, uselessly. The lack of executive leadership results in a lack of cohesion that makes it way down the chain of command. It can even result in different data definitions continuing to exist side-by-side, cluttering the end result and obscuring stated business goals.

The ‘Technology Acquisition’ fallacy

The third, and perhaps most common mistake, is acquiring technology to undertake an Analytics challenge. The technology aspect is bound to be there - in bringing data across disparate legacy systems, often geographically distant, that have been acquired through mergers and acquisitions, for example. But without a methodology that couples technological change to cultural change, the gap between what is desired and what is achieved will be wide.

Next, are the 4 key questions for evaluating an Analytics Roadmap:

Assessment of the current state

In this stage you must clearly define where you are before you set out to your final destination. You need to ask critical questions to probe deeper into understanding for example if the current environment is not meeting the needs of the stakeholders why is that the case? Have there been failures in attempts to implement Analytics in the past, and what were the causes? Clearly if the last one was the case an Analytics Roadmap must also identify not only the root causes, but how this can be solved and prepare the organization for the next steps in implementing an Analytics program.

Determine the ideal future Analytics state

Once the Analytics Roadmap has identified the goals and objectives of the program, it must make the necessary recommendations to achieve them. It determines the sizes and organization of the teams needed. It must also lay out the design of an architecture suitable for the stated Analytics needs requirements, and recommend the appropriate toolsets. Finally, it must include a training and adoption program that meets the individual needs of users and stakeholders.

Addressing future needs

In this part, you must ask how will the plan cope with the currently changing markets and trends? Does it prevent obsolescence in the current investments in technology? Finally, does your Analytics Roadmap leave room for expansion and to further leverage the richness of the company data?

Delivers using a proven game plan

We started with a plan to achieve our key Analytics objectives and goals, but what is the methodology that will be used to implement them? As much as we have scrutinized the roadmap with our team, implementation should undergo just as much rigor if we want to achieve success with our Analytics initiatives. Some tough questions to ask at this stage include: Is this methodology suitable for Analytics programs? How does our Analytics Roadmap itself fit into the methodology? And is the methodology strict, thorough and robust enough to deploy Analytics on an enterprise-wide basis? Finally, what is the track record of the methodology, and has it proven itself in previous deployments?

Conclusion

Clearly avoiding these mistakes is a challenge. It involves asking difficult questions, getting executive support, assessing the current state of affairs as well as a rigorous analysis of the industry to be able to achieve flexibility and ability to adapt in today’s uncertain world. As mentioned in the first paragraph, with a little bit of awareness you can avoid some of the most common mistakes.

Author Bio:

Etienne Castonguay is a founding partner of InEdge (News - Alert), a solution provider specialized in Analytics for the Insurance Industry. Etienne has 25 years of sales management experience in the distribution of information technology solutions. He held the position of Regional Director at Sybase (News - Alert), where he was responsible for starting up the Eastern Canadian operation. He also held various sales positions with Sun Microsystems of Canada and Hewlett Packard of Canada. Etienne obtained a degree in business administration from University of Quebec at Montreal (UQAM) in 1988. See more at: http://www.inedge.com/insurance-business-intelligence-and-analytics/team/etienne-castonguay/#sthash.6ApyEwbi.dpuf