Product-centric approaches make it easier to rapidly innovate and iterate
With the growing use of data and analytics (D&A) across the enterprise, the mindset of the chief data officer needs to shift from focusing on D&A projects and programmes, to driving a product-centric organisation, according to the Gartner Research Board.
“We believe this is the rise of a new type of leader — the CDO 4.0,” says Mario Faria, vice president and programme director at the Gartner Research Board.
Faria explains how this role evolved:
“CDO 1.0 was focused exclusively in data management. CDO 2.0 started to embrace analytics. CDO 3.0 led and participated quite heavily in digital transformation. This fourth version of the CDO is focused on products, and on managing profit and loss instead of just being responsible for driving D&A projects and programmes.”
Traditionally, technology investment has been structured as a pool of ongoing “run the business” costs and a separate portfolio of discrete capital projects that have a clearly defined beginning and end.
However, organisations are now beginning to align funding, development resources and ongoing management support around a set of enduring product lines, says Faria.
Gartner says it expects 72 per cent of organisations to be using the product model this year.
“The change to a product-centric organisation must focus on business areas where there is room to innovate, such as supporting a new business model,” says Faria.
“Product-centric approaches make it easier to rapidly innovate and iterate because they focus on user experience, evolving requirements, and the strategic differentiation for what you are delivering.”
A product-centric D&A organisation requires new skill sets, roles, investment models and the right culture, he says.
Becoming a CDO 4.0
The Gartner Research Board lists three steps CDOs can take as they evolve their roles:
First, think platform first.
When tasked with creating a product, the CDO should plan the D&A platform first, then define the release plan and roadmap.
Following those crucial steps, a team can be built to make the delivery cycle happen.
Faria says CDOs must think about the data first and the use cases later, as shown by leading D&A companies, such as Facebook, Amazon, Google and Apple.
He says these companies have built successful platforms that allow data capture and analytics usage, with faster life cycles between releases.
“Most D&A leaders believe D&A platforms play a meaningful role in their D&A future, though scale and scope differ by company, maturity and investment levels,” says Faria.
CDOs who are able to deliver results using an operating model that hides details and is focused on the better, more scalable usage of the data assets, will succeed
Second, change investment models.
CDOs should work with their organisations’ leaders to adapt or change the investment models their businesses currently have in place, says Faria.
Serving one area or one team on an individual basis is not scalable anymore. CDOs should look to scale the usage of the platform across the enterprise.
In the product line management model, product lines are funded based on the business capabilities they support.
Common or shared capabilities - such as infrastructure, technology, D&A - are funded based on the anticipated and aggregated needs of the product lines they support.
Third, use a proven product management methodology
CIOs and other cross-functional executives, as well as business unit leaders, must set the tone for the importance of product management in driving successful growth and scale, says Faria.
It is critical that the definition of the role is clear to all stakeholders, says Faria.
Fundamental to the role definition are its vision and objectives, goals, and scope and metrics - specifically, the metrics for transitioning toward a customer-centric approach for innovation.
Faria says not all CDOs will be able to make the transition from a project or programmes mindset to a product mentality.
“CDOs who are able to deliver results using an operating model that hides details and is focused on the better, more scalable usage of the data assets, will succeed.”
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