Simply Business Simplifies & transforms insurance experiences with data
Customer Company Size
Large Corporate
Region
- Europe
Country
- United Kingdom
Product
- Looker
- Snowplow
- Snowflake
- Amazon SageMaker
- Kafka
Tech Stack
- Data Build Tool (dbt)
- Twilio
- Google AdWords
- ExactTarget
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
- Brand Awareness
Technology Category
- Analytics & Modeling - Real Time Analytics
- Analytics & Modeling - Big Data Analytics
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Predictive Maintenance
- Supply Chain Visibility
- Regulatory Compliance Monitoring
Services
- Data Science Services
- System Integration
About The Customer
Founded in 2005, Simply Business provides an online brokerage service, delivering policies tailored to individual business requirements. The company specializes in public liability insurance for small to medium enterprises (SMEs) and insures over 750,000 small businesses and landlords. Using the power of technology and data, Simply Business has transformed the client experience and become one of the UK’s biggest business insurance providers. Since 2014, Simply Business has leveraged Looker to streamline data access and deliver actionable insights across the organization. Over the years, they’ve found new ways to customize the way their employees experience and take action with data.
The Challenge
Before implementing Looker in 2014, Simply Business did not have a centralized data platform or process, which resulted in challenges bringing siloed information together and accessing consistent metrics. Without a single source of truth, many decision-makers across the organization spent their time manually creating their own reports. However, many of these reports and metrics didn’t match up, which led to confusion and mistrust of data, and ultimately delayed decisions and action. The insurance brokerage needed a single source of truth to unify data across its multiple applications. Additionally, since insurance is a highly-regulated industry, it was critical that information be consistent, auditable, and secure.
The Solution
Initially, Simply Business adopted Looker to analyze, explore, and deliver insights from Snowplow event data on top of their data warehouse. However, employees quickly introduced new use cases, including marketing analytics to better understand their pay-perclick (PPC) spend on Google AdWords, as well as their website traffic and conversion rates. Simply Business built a contact centre application called Idiophone using Twilio’s communication platform. The 'data ‘n analytics' (DNA) team was looking for new ways to help the organization discover value with data, and they saw this as an opportunity to make an impact — while further increasing Looker adoption. To ensure success, they focused on making day-zero reporting available in Looker so that stakeholders could gain immediate insights into call centre activities and speed up end-of- term closing reports.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Remote Temperature Monitoring of Perishable Goods Saves Money
RMONI was facing temperature monitoring challenges in a cold chain business. A cold chain must be established and maintained to ensure goods have been properly refrigerated during every step of the process, making temperature monitoring a critical business function. Manual registration practice can be very costly, labor intensive and prone to mistakes.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Asset Management and Predictive Maintenance
The customer prides itself on excellent engineering and customer centric philosophy, allowing its customer’s minds to be at ease and not worry about machine failure. They can easily deliver the excellent maintenance services to their customers, but there are some processes that can be automated to deliver less downtime for the customer and more efficient maintenance schedules.
