Where Are You in Today’s Analytics Journey?


Indellient has released its exclusive industry report from the Insurance Analytics Canada Summit. Download it now.

The analytics era is in full-force, where organizations are looking to move beyond the traditional data warehouse.

Data and analytics have transformed many areas of life – yet the insurance market still lags behind other fast-moving industries. Implementing data and analytics is no longer an option, but essential for those organizations wanting to increase their bottom-line and keep up with the pace of competition.

This is why Insurers flocked to this year’s https://www.indellient.com/blog/re-cap-indellient-attends-insurance-analytics-summit-2017/, and why we exhibited our analytics offerings to those needing assistance in how to succeed in this vast arena.

We wanted to be a guiding light to those struggling with their IT, and find out what keeps these organizations up at night.

But the first and most crucial step was to identify where they stood in their analytics journey, before helping them realize their goals. We introduced an interactive avenue for organizations to pinpoint exactly where they stood.

We polled the audience on their analytics maturity stage. Scroll down to view the results.
We polled the audience on their analytics maturity stage. Scroll down to view the results.

Booth visitors got to not only stop and take a hard look into their organization and answer this question honestly without judgment, but also got to compare their progress with others of the same caliber.


The majority of participants (54%) identified themselves at the second stage of the analytics journey. In this phase, data scientists extract valuable insights and collect new, large sets of data – though their analytics approach lacks sophistication.

To our surprise, 33% of participants described themselves at the very basic level of using traditional analytics, where structured data is sourced internally and in small volumes. In this stage, analysis is not seen as a basis for competition and is performed by small teams.

A smaller majority of participants (a staggering 13%) found themselves in the third phase of the analytics model, where analytics is used in the operational and decision-making processes across the organization and using more complex methods to analyze their data.

Though, the analytics journey is just that – a journey that consists of mistakes, hurdles, learning opportunities and efforts that eventually pay off in the long-run. And though many insurance organizations are in the initial phases, it doesn’t mean they cannot advance to the next phase and leverage the power of data and analytics to succeed.

Barriers to Maturity

Many of today’s organizations, especially an age-old industry like insurance, struggle with implementing analytics to improve end goals, customer satisfaction, and experience.

Canadian insurance customers expect their data to drive seamless, personal and hassle-free experiences, from search to claim. Greg McCutcheon, President of Opta Information Intelligence explains: “The period between understanding the customer journey and delivering on experience has to condense. The consumer is demanding it. If the industry is unprepared it will be disrupted. I would rather be a part of the change, leading it rather than waiting to see what will happen.”

As well, initial start-up cost vs. time to delivery is a key issue with analytical efforts. It’s difficult for major stakeholders to understand that short-term ROI loss will lead to long-term ROI gain. Experts at this year’s conference recommended that 75% of resources should be allocated towards fast ROI efforts, while the other 25% towards longer projects.

Also, most firms find that they cannot keep up with the analytical capabilities of modern technologies, and fail to adapt. They don’t carry enough knowledge on analytics to make an informed choice of what model/approach to take for specific business cases.

“The biggest obstacle I see is cultural willingness to embrace the fact that nobody has all of the data. Insurers really have to get their minds around the fact that there is a wealth of information outside their business,” McCutcheon warns.

Though, anyone who is willing to put in the time to reap the many rewards of implementing analytics into their business can prosper with the right tools and assistance.


Data has the potential to dramatically simplify and speed up the insurance process. For the most part, Insurance companies know what data they have and know their end goal – they just don’t know how to get there.

Experts advised that it’s important that analytical teams work very closely with customer experience/satisfaction teams to ensure that customer end goals are being met, as well as design teams responsible for customer engagement platforms.

As well, keeping analytics agendas moving forward will have a trickle-down effect on all other business processes; hence, should be at the forefront of business practices.

“There is a huge opportunity to use data and technology to drive workflow efficiency. Too often insurers have become enamoured by a particular process because it’s a cherished workflow. Adding value to services that no-one knew existed, that’s going to change the experience of insurance,” says McCutcheon.

Organizations need to continue to invest in budget allocation towards analytics regularly, instead of it being an afterthought.

Frequently Asked Questions

  1. How can we empower our IT teams with more resources for analytical models?
    • Experts indicated CEOs and stakeholders need to invest more resources in hiring more IT talent and educating their current employees.
  2. How can we attract more analytic expertise within our organizations? (e.g. data scientists, etc.)
    • Experts said this is difficult for two main reasons:
      • IT experts typically prefer to work for IT organizations; and
      • Salaries typically are not as competitive in insurance as they would be in an IT enterprise.
  3. How can we get started today?
    • The first step is evaluating your pain-points and identifying what you wish to use analytics for, whether it’s to predict future outcomes, better understand your customer base or make better decisions, faster. Next, is trusting a dedicated team of data scientists, business analysts and data fanatics to help you with your journey.