If Technology
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If Technology

The Rise of Data Products and Their Owners

How If’s data product owners are helping data consumers to create value.

Source: https://littlevisuals.co/

If’s data & analytics landscape

If is, arguably, a data driven company. We are the largest property & casualty insurer in the Nordics. The key ingredient in our products and their development is data. It doesn’t get much more data intensive than that. We are also heavy users of data in sales, marketing and customer service operations, including our claims handling.

Our data landscape is characterised by a relatively large number of data producers. Majority of these are insurance systems of various kinds but also e-commerce, marketing and customer service solutions contribute to the growing data volumes and complexity.

On the data platform side, we have worked rigorously in the past years to bring data from our insurance systems to the same data model and to a common Enterprise Data Warehouse (EDW) on Teradata. The ability to easily combine data from several data producers within the same area/domain across the Nordics has been a key requirement from our data consumers (the reports of death of EDW are greatly exaggerated). Our Teradata EDW is accompanied by a cloud based data warehouse on Google BigQuery that is primarily used for web and marketing related data.

Our Nordic data analytics community is somewhere in the excess of 100 analysts and data scientists. The BI (Tableau) user base has grown in the recent years to around 5 500 content creators and explorers. This puts tough requirements on the quality, usability and governance of data.

So, to summarize, there are three important factors that influence our data governance strategy.

1. A large number of different data producing systems that are business critical and interesting for data consumers.

2. The usability of data needs to be high to enable data driven decision making, also by those with limited data and analytics competence.

3. Data consumers wish to utilise raw data from various data producers as well as modelled and standardised data, that is, combining data from several data producers within a specific area across multiple countries.

Clearer ownership, stronger vision and improved usability of data

Our data asset development has historically been relatively technology driven, and rightly so, as our grand ambition has been to establish a common enterprise data warehouse entailing development of a large number of ETL/ELT processes (i.e. just getting the data to the same place).

To avoid a disconnect between the technical development of our data assets and their consumers and to ensure value generation from our data, we wanted to become more user driven in our approach.

We, as many others, have been inspired by Zhamak Dehghani’s recent work on product thinking and distributed ownership in the context of data.

“…domain data teams must apply product thinking with similar rigor to the datasets that they provide; considering their data assets as their products and the rest of the organization’s data scientists, ML and data engineers as their customers.”

The notion of treating data as a product resonates well in the organisation and it naturally brings about a strong ownership and accountability in the form of product owners. Again, a concept that is well established and understood by the organisation.

Our approach has been to apply the essence of Dehghani’s product thinking to the data assets already available on our data platforms in order to provide clearer ownership, stronger vision and improved quality and usability of data.

Data consumers wish to utilise data with different degrees of standardisation. This is facilitated by data products and their owners.

In practice this means that we have a number of different data products covering the key areas in our business (e.g. Sales, Claims, Customer, Policy/Agreement, Web & Marketing) with a dedicated Product Owner in each who is the data consumer’s main point of contact in all matters related to the data within the area. These products have their own backlogs and dedicated development teams. The coordination between the Data Product Owners is facilitated by the Chief Data Product Owner.

The visionary data product owner

The role of the Data Product Owner is naturally crucial in this governance setup to enable and support the data consumers to create value. We have agreed on a few key principles for the Data Product Owner role.

As a Data Product Owner…

1. I have a clear vision and a roadmap for the data product I own.

2. I ensure that my product is discoverable, highly usable, legally compliant and has good quality.

3. I consider my data product an important asset for the whole company. I promote and evangelise the use of my data product.

4. I collect and prioritise data development tasks from the whole organisation.

5. I have a good understanding of the data itself and how it is accessed and used throughout the organisation.

6. I use 50–100 percent of my time on this role.

Experiences so far

It may seem obvious, but the most noticeable effect of introducing data products and their owners has been the improved clarity of ownership and responsibilities. In practice, our data consumers (analysts, data scientists, data engineers, controllers, business developers and the like) now know who to contact with their data questions. This is appreciated.

Similarly, the vision of our data assets has been strengthened, much thanks to the Data Product Owners that have really embraced their roles and are passionate about finding ways to enable data consumers with their products.

We have also witnessed a better alignment between the business and IT resources in our EDW leading to faster and more relevant development work.

There are naturally still challenges and potential for improvement. For instance, we would likely benefit from clarifying and strengthening the role and responsibilities of Data Producers in our organisation.

So far, though, forming data products has been a step in the right direction — the journey continues.

Note: this article is related to data governance in If’s B2C business.

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