How to Value AI, Analytics Initiatives

Here are five models that can be used to ensure that the value of AI and data analytics work is recognized and valued appropriately.

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--None of the models singly can offer a solution, but, used together, they offer a compelling structure to power the pursuit of business value from data, analytics and artificial intelligence.


Data, analytics and artificial intelligence (DAAI) agendas are now a part of boardroom discussions at all insurance companies, and what's the next big shiny thing is hotly debated at coffee tables at most insurance companies.

However, determining how much business value comes from DAAI efforts remains difficult. So does deciding who is responsible for ensuring that business value is measurable and sustainable.

We will delve into few value realization models that insurance firms can follow to deal with this conundrum and ensure that data, analytics and AI (DAAI) initiatives remain at the top of business agendas effortlessly.

1. Strategic Alignment Model

Insurance companies using this model have execution of DAAI across the company as an organizational strategy itself. DAAI capabilities are so pervasive that they influence strategic priorities or metrics in the first place.

With this model, questions around the value of DAAI do not have a direct, measurable answer. The strategic agenda alignment model requires a high level of organizational maturity. It is sustainable in the long run.

2. Pain-Point Model

This model uses DAAI to address opportunities and risks that keep the C-suite awake but primarily looks at addressing the pain points. This method follows an iterative process of identifying pain points, collecting data to validate each pain point, establishing DAAI initiatives to address prioritized pain points, implementing solutions and measuring benefits.

This is an effective tactical approach. It also helps build a data-driven culture. Typically, the value creation responsibility is a joint ownership between the respective C-suite executive and DAAl leaders.

3. Customer-at-Center Model

Insurance company operations are inherently complex, with most of the activities geared toward smoothing customer journeys across buy, service, claim and attrition points. Therefore, measuring value created by DAAI initiatives at customer touch points is a reasonable metric, although it does not account for the value created by operational efficiency enhancements.

Assessing, measuring and attributing value created by DAAI in the customer-centric model is a fairly straightforward task and ensures that capital is deployed to enhance the experience of the most important stakeholder of the insurance company, its customers. Value creation in this model is measured at customer touch points so it comes under the remit of teams and tools enabling such journeys.

4. KPI Model

Key performance indicators (KPIs), along with their owners and drivers, are essential for an effective and efficient insurance operation. Any initiative that improves KPIs creates business value, and DAAI initiatives can do so. 

Because organization KPIs and monetary gains are intertwined, however, value may be created but not be adequately showcased.

An organizational KPI model is a logical one to adopt. The individual KPI owners have responsibility for improvement, with a linkage to the DAAI team.

See also: Life Is a Bowl of... Customer Analytics

5. Technology Showcase Model

Adoption and proof-of-value are good surrogates for value creation here. Extrapolation and scenario analysis of future value using present outcomes, albeit limited, also provides good visibility into value.

DAAI teams are responsible for sustainability, measurability and visibility into value.


Ensuring business value from DAAI initiatives does not have a one-size-fits-all solution. There needs to be a single-minded focus on creating measurable and sustainable business value.

None of the models singly can offer a solution, but, used together, they offer a compelling structure to power the pursuit of DAAI business value.

Gaurav Porwal

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Gaurav Porwal

Gaurav Porwal is an accomplished business leader with two decades experience of creating business strategies centered on analytics, data science and data-led transformation.

Porwal has been in leadership roles in business analytics, risk management and customer value organizations at global banks, insurance companies and global conglomerates. He has deep expertise in banking and insurance products, bancassurance, insurance strategy and operations and retail banking risk and customer bureaus.

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