McKinsey has released a report stating that most insurance companies in Europe, the Middle East, and Africa (EMEA) are investing in advanced analytics (AA). However, most fail to capture value from it.
The article offers several reasons for this.
A lack of C-level sponsorship: Many insurance businesses lack support and sponsorship from top-level executives for analytics initiatives. Without the backing and advocacy at the highest level, it becomes challenging to prioritise and allocate resources effectively.
Insufficient alignment with the business: There is a disconnect between analytics teams and the broader business objectives. Without proper alignment, analytics initiatives may not address the key challenges and opportunities that the business faces, leading to limited value creation.
The slow, siloed, pace of use case development: The development of how AA is used in the organisation’s departments is often slow—taking nine to 12 months per instance—and siloed. These traits hamper the ability to realise value quickly and limit collaboration between teams.
Lack of clear vision and link to value: Data assets and technical infrastructure are often built without a clear vision or a strong link to value. Without these, the company has no way of using analytics to drive better outcomes.
Weak foundations in data, talent, and technology: Many insurance businesses struggle with inadequate data quality, talent shortages, and outdated technology infrastructure. These foundational issues hinder the effective implementation and scaling of AA initiatives.
Inadequate tracking and assessment of impact: A significant number of businesses in the insurance industry do not track or validate the impact of their analytics initiatives. Without monitoring and measuring the impact, it becomes challenging to understand the value created and make informed decisions about future investments.
Poor data infrastructure and management: Data-related challenges—such as poor governance, data quality issues, and limited data availability—remain roadblocks for many insurers. Improving data infrastructure and management practices is crucial for scaling the value realised from the intelligence gathered through analytics.
Underinvestment in analytics capabilities: Many businesses commit relatively low investments to analytics, which can limit the scope and impact of analytics initiatives. That, in turn, means leaders see less value in these capabilities, resulting in even lower funding going forward. That is why increasing investment in data, talent, and technology is necessary to accelerate the value capture from AA.
Keeping these factors in mind, the report offers four ways of scaling the impact from AA faster.
Create a strategy that maximises value: Successful insurers in the EMEA link analytics initiatives to business strategy objectives. They prioritise use cases based on measurable value. Then, they invest in data, talent, and technology accordingly. This appears to give them an edge over others in gaining value from AA.
Take a domain-centric approach: When using AA, the more applications a company has, the better the performance. Instead of focusing on one or two instances per department, leaders in AA use it for a range of applications within the domain. That way, intelligence from one area can be used to enhance capabilities in others. That is something most insurers are not doing.
Align analytics execution with the business: For AA to provide maximum value to insurance businesses, it needs executive-level accountability, senior-business sponsorship, and cross-functional teams with domain experts and analytics translators. Iterative ways of working and a “test and learn” mindset enhance speed and effectiveness.
Invest in the right resources: To derive value from their AA goals, EMEA insurers need to invest in data, talent, and technology. This will give them a competitive edge in the insurance industry.
Insurance businesses may find it easier to implement effective AA as digital transformation is affected through insurance software platforms, like Zinnia. These provide analytics as part of their cloud offerings. However, how businesses use this feature is still dependent on them and their teams.
Parul Mathur has been writing since 2009. That’s when she discovered her love for SEO and how it works. She developed an interest in learning HTML and CSS a couple of years later, and React in 2020. When she’s not writing, she’s either reading, walking her dog, messing up her garden, or doodling.