Data-driven Operating Models

Aurora’s COO Jiwan Laly on why the need for data begins right at the point an operating model is initiated.

How to understand Data-driven Operating Models

Let’s start with a simple question: What is an Operating Model? It is often described as the connection between an organisation's strategy and making that strategy a reality. If the strategy gives you the what, the operating model shows how the various elements of the organisation come together to deliver and create value. 

Creating a target operating model also helps to identify the gap between what an organisation looks like today compared to what it needs to look like tomorrow.

A concept I have found useful is the one that describes the operating model as the plans for building a new house. I’ve never been involved in a new house build but recently I had extensive work done on my existing home, including the building of an extension. The architect meticulously measured the current rooms and garden space as well as ensuring the size and shapes of the new areas were specified. The structural engineer performed many complex calculations on the beams and weight-bearing walls.

My plans would have been useless without the data that underpinned the build. When the builders arrived, they had all the details – not just the shape but the size and the cost parameters they were working within.

It’s not exactly the same as a business operating model, but similar principles do apply. In many of the business models I have designed, data is an orphan, often running as a separate program not even connected to the Target Operating Model initiative. I find this bizarre as no-one is better placed to look across organisational silos as the people involved in designing the TOM and the end-to-end customer journeys.

The need for data starts right at the point that the operating model is initiated – decisions on the shape and structure of teams and processes all require data, not hearsay (otherwise it’s a bit like the structural engineer leaving his tape measure at home.)

The requirement doesn’t go away once you have a design. Customer demand for digital access and the organisation’s need to reduce cost has made connectivity of customer data even more critical, but many Financial Services organisations are struggling with making it real. 

In the CLM (Client Lifecycle Management) space, this demand is reflected by the need to deploy global regulatory policies; to contact the customer once but to know them across jurisdictions and products; to enable digital access as part of the broader digital journey; and to reduce cost by using external, trusted sources to drive the work rather than periodic reviews of static customer profiles.

These all require an operating model built on knowledge of how the data will support and connect the journeys. Data collected while the sales teams are prospecting becomes the basis of the KYC (Know Your Customer) record; data collected at onboarding, the basis of the product and account data; and the account data, the basis of regulatory reporting. The operating model must consider how the disparate technologies, all with their own master records, will be brought together to create a shared data source that can be accessed by multiple systems and for customers moving between digital channels.

Data is the water and electricity that flows through the pipework and wiring of the business processes, as defined by the operating model. Siloed bits of pipework and wiring, therefore, won’t feed the correct content to where it’s needed to achieve the architectural vision we started with.