How to develop a data-driven business strategy
There is no guesswork in the world of business. A staggering 70% of businesses fail within 10 years due to lack of preparation, insufficient market demand or an inappropriate business model. There are areas in life where “winging it” is appropriate.
Running a business isn’t one of them.
Creating a data-driven business strategy can be a pivotal first step in avoiding these pitfalls. For example, businesses that embrace customer analytics as part of a data-driven business strategy are 23x more likely to acquire customers than those that don’t. They’re also 19x more likely to be profitable than those not yet analysing data to support their business decisions.
Insurers have long understood the importance of analysing data to assess risk and calculate premiums. Today, forward-thinking insurers are investing in new technologies to enable data to be used more broadly across all areas of their business. Despite the financial challenges of the pandemic, 96% of US insurers are accelerating digital transformation initiatives, with 68% planning to increase spending on data analytics.
As many are now realising, the winners of tomorrow will be those who create and execute a data-driven strategy today.
How to create a data-driven business strategy
People and businesses are creating and consuming more data than ever before. This data presents a huge opportunity for insurers if harnessed correctly. Insurance leaders must therefore have compelling and clear objectives for their data strategy. They must also gain alignment and motivate other decision-makers and stakeholders in implementing new data initiatives.
When first adopting a data-driven approach, it’s not nearly enough to ask technology teams to enable Big Data to be displayed on a dashboard. Instead, you must first decide what business objectives you are trying to achieve and then consider what data would help you do this.
This is just the beginning, however.
Quality data, powered by technology
Data scientists have a saying “garbage in, garbage out.” That is to say, any data-driven initiative is only as good as the data on which it is based. Therefore efforts must be made to ensure high-quality data input.
The insurance industry is known for possessing a mountain of data. Traditionally, much of this data has been locked away in silos due to legacy infrastructure, or inaccessible in other third-party systems. As a result, insurance companies have had to make do with historical data or information provided by customers to make business decisions.
However, innovations in data storage, processing, and retrieval are helping the insurance industry put this mountain of data to use in a number of innovative ways.
Modern cloud-based data platforms can collect, consume and process raw data from multiple sources via APIs, enabling insurers to access more accurate data in real-time. It is therefore essential that insurers invest, partner or acquire to build out their capabilities in these areas as part of their data-driven strategy.
Once this infrastructure is in place, you’ll be able to integrate data-driven insights into your business strategy across the entire organisation. You’ll also be able to measure your results and gain valuable insights that will help you refine your strategies as you go.
Identify use cases for your data
To get the most out of your data, you need to identify potential use cases that are likely to have the most impact on your strategic objectives. In the insurance industry, several use case trends are already starting to emerge for risk pricing, customer experience and claims processing.
Automated pricing and risk analysis
With Big Data underwriters can access vast quantities of accurate information and build sophisticated models that allow pricing at an increasingly granular level. For example, in SME insurance, where underwriters would previously have relied on information provided about a business by their broker. Today, they could plug directly into that business’s accounting software to access multiple years of company financials.
Insurers are not the only ones who stand to benefit from harnessing data. Huge improvements can be made in customer experience with relatively simple use of third-party data. These could include automatically retrieving data from third-party sources to reduce data entry for the customer. This would make signing up for new policies quick and painless.
New technologies, like Artificial Intelligence (AI) and Machine Learning (ML), can also play an important part in processing claims. Automation has already come a long way in this area, with many straightforward claims now processed by simple ‘If X then Y’ rules-based decisions. AI and ML present the next evolution of this automation, enabling more accurate and quicker claims, even in more complex cases.
Using data to reach strategic objectives
Once a high-value use case that aligns with your strategic objectives has been identified, start implementing your data-driven initiatives. Data-driven initiatives need to be dynamic in order to improve and continue delivering great insights. For this reason build, measure, learn and implement your next data initiative based on your findings.
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Establish a repeatable process by considering what data should be measured, track the outcomes and plan for how results will be collected and analysed. This is data science, after all. For something to be scientific, it needs to be measurable, verifiable, and repeatable.
The role of data in insurance
Good analytics are exceptionally important where an in-depth understanding of your customer and the risk they present is required.
A regular retailer might have a business goal of attracting more customers between the ages of 20 and 50. To implement this they would create a product and a marketing campaign to appeal to that demographic and then track customer data. The cost of providing that product would remain the same regardless of who buys it.
As an insurer, you have more specific needs. If you provide health insurance to customers between the ages of 20 and 50, your pricing will be determined by their age, medical history and other factors such as their BMI. As their insurer, you might want to reward them for healthier behaviour with lower premiums or increase it if they suddenly take up smoking.
As you can see, it doesn’t take very long at all for the complexity to get quickly out of hand.
The role of today’s insurer is shifting from pure protection towards a more preventive one. New data-driven initiatives, like real-time data, can help customers reduce their risk, and ideally benefit from discounted premiums.
Insurers can improve their understanding of a customer’s potential risk at the point of purchase by integrating with third-party sources for historic and real-time data. Ongoing consented access to these data sources can lead to the creation of products that adapt dynamically as the policyholder’s risk levels change. It is also known as “connected insurance”.
Data and analytics in the insurance industry can be combined to measure and optimise everything, from risk assessment to cost analysis to improved customer experience. When it is aided by cutting-edge cloud computing and machine learning, processes and calculations can be streamlined to set your business up for success!
Data-driven business strategy isn’t going anywhere. If anything, we’re going to just keep creating more and more data especially with emerging new technologies like the Internet of Things. Putting a data-driven business strategy in place ensures you’ll be able to stay at the head of the pack.
Looking for new technology to enable data-driven insurance?
The objectives of your data-driven strategy can be achieved with technology that can leverage third-party data, automation, and machine learning.
Data-driven strategy with a digital and connected approach is changing the insurance landscape and creating incredible opportunities for insurers and their ecosystem partners.
To learn about how data will transform insurance companies and how they engage with their customer watch the roundtable on Insurtech trends: The future of connected insurance