Sisense analytics tools drive Hastings Mutual’s growth


In just over a year after starting to use the Sisense analytics platform, Hastings Mutual Insurance Company has improved efficiency, identified new sales opportunities and increased revenue.

Hastings Mutual, founded in 1885 and headquartered in Hastings, Michigan, is a property and casualty insurance company that operates in the Midwestern states of Illinois, Indiana, Iowa, Michigan, Ohio and of Wisconsin.

Sisense, on the other hand, is a New York-based analytics provider founded in 2004, offering a platform that serves both trained data scientists and self-service business users.

Growing demand for data

In 2020, more and more Hastings Mutual employees wanted to use data to inform their decisions, whether they were part of the head office or field agents working for affiliated agencies.

According to Randy Sykes, IT director of data services at Hastings Mutual, Hastings Mutual had started building its data warehouse about seven years earlier, and data had finally reached a level where data consumers trusted it and could be informative. .

We had a lot of delay for the company to see the data we collect. The data was at a level where people could use it, they trusted the warehouse, and there was an explosion of people wanting to access the data.

Randy SykesIT Director of Data Services, Hastings Mutual Insurance Company

Hastings Mutual was using Pentaho for its business intelligence needs at the time, but using the platform required a level of technical knowledge that most of those suddenly requesting data didn’t have, Sykes said.

It was a solid platform for those who had Sykes’ expertise and were the ones who built dashboards and other data assets, and Hastings Mutual still uses Pentaho for its mining, loading and transformation. But if it was to enable self-service analytics, the company needed a platform that employees with no experience in coding, statistics, and data science could use.

Additionally, without self-service capabilities, those suddenly requesting data essentially had to queue for a small, centralized data team to respond to requests. By the time they finally got their hands on data that could inform their decisions, the data was 30 to 45 days old, according to Sykes.

“We were way behind schedule for the company to see the data we collect,” he said. “The data was at a level where people could use it, they trusted the warehouse, and there was an explosion of people wanting to access the data. Pentaho was designed for people with a technical background, and we so started looking for a tool that was much easier to use.”

Choose Sisense

When looking for a new analytics platform, Hastings Mutual tried Qlik and Tableau in addition to Sisense. Ultimately, Sisense’s data modeling capabilities made it the ideal analytics platform for the insurance company.

“One of the features of Sisense that others didn’t have as much was the ability for us to create data models that people could then extract their information from,” Sykes said. “Rather than people having to familiarize themselves with the underlying raw data, Sisense allowed us to build models that people could object to, instead of having to learn all the technicalities of the information. .”

A sample dashboard from Sisense displays revenue data for an organization.

Hastings Mutual rolled out Sisense in October 2020 and has since empowered its employees to work with data in a variety of ways.

Some data is still analyzed by Hastings Mutual’s centralized team. But Sisense has strong built-in analytics capabilities. Sykes and his team now embed reports and dashboards on his agency’s website so agents have data directly in their workflows.

Additionally, for those with some familiarity with analytics by working with reports and spreadsheets, Sisense is easy enough to use for some Hastings Mutual employees to take advantage of the platform’s self-service capabilities. to analyse.

When Hastings Mutual started using Sisense, it had seven business users. Today, it has 20 designers and more than 100 people using about 200 dashboards that have been created and are automatically updated nightly, according to Sykes.

“My team is still responsible for collecting the data and making sure it’s been properly brought into compliance,” he said. “But we wanted to make sure we were getting the data into the hands of our decision makers.”

Results

The data that Hastings Mutual collects daily includes system of record data, namely policy, claims, accounting and financial data. Additionally, each day it collects weather and climate data from the National Oceanic and Atmospheric Administration, weather data from Iowa State University, and census data.

Weather data is important to insurance companies because weather risk insurance often covers unforeseen events, and by understanding weather patterns and trends, insurance companies can mitigate their own risks.

Meanwhile, one of the benefits of Sisense is that Hastings Mutual is able to combine capabilities developed by itself with those provided by Sisense to customize analytics assets such as geospatial maps. Hastings Mutual may overlay data such as weather information, census information and information by county or agency.

Ultimately, in about 16 months, the Sisense analytics platform helped Hastings Mutual identify $50 million in upsell opportunities and increase revenue by 2%, according to the company.

“We talk about upselling opportunities, but what we’re really doing is presenting our agents with a list of policies where opportunities exist, which helps the agent get better deals,” said said Sykes. “Our business has been fundamentally strangled [before adopting Sisense]. They didn’t have enough information coming their way.”

He added that conditions change rapidly and without current data, decisions made are not well informed.

“We really need to be able to provide insight into what’s happening in our business very quickly,” Sykes said. “We can’t wait 30 days for a mainframe. The most important thing is just to be able to show our people the information they’re looking for, and Sisense has helped us do that faster. The data is great, but if you don’t can’t do it, it’s no use to you.”

Future plans

Beyond data modeling, embedded analytics and self-service BI, Hastings Mutual plans to expand its use of Sisense, according to Sykes.

It does not currently take advantage of Sisense’s natural language processing capabilities, but in an effort to enable more non-technical users, it plans to implement natural language query functionality. Additionally, Hastings Mutual plans to use Sisense BloX, a set of pre-built templates that allow users to create custom apps.

“Right now, we’re letting our clients digest what we’ve already presented to them,” Sykes said. “We see a lot of opportunities. It’s just a question of which is more important to start with.”

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