As organizations continue to grapple with digital transformation projects, chief data officers (CDOs) can help drive those digitalization objectives by ensuring their data and analytics (D&A) activities are aimed at producing desired, and measurable outcomes.
By focusing on revenue-generating objectives and data-monetization goals, CDOs can help organizations capitalize on their valuable data resources.
At their core, digital transformation initiatives are data projects in that they traditionally fall under the category of automation or the customer experience.
In the former, it’s tightly correlated to AI/ML initiatives that necessitate data at the core to measure, train, action, re-train and learn.
“The CDO must be an active – if not responsible – player there,” said Anand Pandya, global head of financial services for Hakkoda and formerly CDO for Curinos.
He explained the customer experience aspect of digital transformation is the understanding that the customer’s process will go from physical to digital, and thus the digitization of a product or service and its monetization strategy become a data-centric exercise.
“There’s no separation between a data project and a digital transformation initiative,” Pandya said. “It falls to the CDO to ensure that they are part and parcel with other C-suite leaders to make the data a first-class asset in the initiative from plan to measurement to action.”
Because data-driven decision making is essential for organizational success, CDOs must be able to effectively communicate the value of data to those who are not data literate.
“What better way to do this than to focus on one of the largest areas that impact the business—revenue,” said Emad Hasan, CEO of Retina AI. “By doing so, they will be able to create a data-centric culture that can drive competitive advantage.”
This means CDOs should seek out data projects that focus on revenue generation, data monetization and productization.
Hasan explained marketing, finance and product teams are always looking for ways to increase revenue and grow their customer base, but they often don’t have the time or expertise to effectively collect and analyze data.
“That’s where CDOs come in,” he said. “By partnering with these teams, CDOs can help marketing, finance and product teams identify projects that focus on revenue generation, data monetization and productization.”
For example, marketing may want to segment the customer base and develop targeted marketing campaigns.
Finance may want to better understand their customers’ lifetime value (CLV) to make more informed investment decisions, and product teams may want to develop new features or offerings based on customer feedback.
“By working with CDOs, these teams can leverage data to achieve overall revenue goals,” Hasan said.
For Pandya, “transforming digitally” implies that the customer experience and the processes tied to fulfillment of a product or service are moving from a central/physical arena into a decentralized/digital realm.
That goes beyond “just” technology, but it ties to the realization that a digital component or process generates data.
“The digitization of a concept enables the measurement of the bespoke concept through its data,” he said. “Ultimately, the business can’t separate a digital transformation of its revenue process from a revenue generation data project, as they are one in the same.”
From that perspective, the CDO’s role has a bigger and brighter spotlight to enable robust insights and agility to adjust to the customer needs in a digital space.
Pandya explained that more often than not, the formation of the chief data officer is the recognition that data is an asset in the organization that necessitates its own strategy and value creation.
“If a CDO’s focus lies in enablement projects such as governance, literacy, compliance, risk and so on, then they’re often couched as ‘just technology’ and either get slotted down under a CIO or CTO, or see their initiatives sputter and fail,” he said. “The lack of connective tissue between how and why fails to demonstrate the value of data.”
However, CDOs that emphasize a value-generating project and monetization goals close the gap between data the asset vs. data the technology.
“A CDO that can pair off revenue-generating, customer-service value alongside data quality and literacy initiatives is going to see more success,” Pandya said.
He added when it comes to data and business improvement, the top objective for CDOs in 2022 should be innovation, either through the combination of existing data assets to create a newly curated asset (the “1+1=3” phenomenon) or the expansion of availability and brokering of data access (EDI, Snowflake’s Data Cloud Marketplace, etc.).
The second objective he defines as analytics/AI/ML initiatives, which encompasses the enablement of automation to create organizational efficiencies and effectiveness, clarity in analytics providing value to the organization (breaking down silos and solving the “paralysis by analysis” paradox) and linking the operations of data and analytics to prioritized and quantified business outcomes and metrics.
From his perspective, the CDO must be an “intrapreneur”, which means CDOs and their office must chase the business and find the value-adds.
“Go to stakeholders, go to lines of business, go to the field and evaluate opportunities for an analytics project that can demonstrate a tangible business value,” he said. “Not everything has to be seismic, and not everything has to be a flamethrower. If you’ve only a lighter, don’t boil the ocean, go find a tablespoon. Prove it works, then go tackle the next big thing.”
Pandya said ultimately, the lack of understanding is the biggest downfall of the office. If the CEO isn’t clear on what the CDO does, then it’s difficult to chart and define success criteria.
“If the clarity doesn’t exist, it undermines the ability to garner stakeholder support and involvement,” he explained. “Without that, there’s no resources or funding or focus on the right initiatives. Depending on the organization’s structure, there may not be authority to execute responsibilities.”
Pandya said a CDO must balance on the knife’s edge of understanding foundational technologies, data, and the lack of governance or literacy around it against the value creation and business alignments that data strategy provides.
“Removing bureaucracy, clarity in purpose, and clarity in impact allows a CDO to create an action plan to get past barriers and roadblocks to success,” he said.
Hasan added one of the biggest challenges faced by CDOs is data literacy.
“Too often, data is seen as something that belongs in the IT department, and as a result, business users don’t have the skills or knowledge to make use of it,” he said. “This lack of data literacy prevents CDOs from being able to drive data-driven decision making across the organization.”
He explained another major barrier to success is departmental silos, where data is siloed within departments, making it difficult for CDOs to get a holistic view of the organization.
“This can make it difficult to identify patterns and trends, creating barriers to success,” he said. “These are just a couple of the major barriers to success for CDOs.”
While data literacy and departmental silos can be major obstacles, Hasan said they can be overcome with the right approach.
“By working closely with business leaders and breaking down data silos, CDOs can overcome these challenges and drive successful data and analytics initiatives,” he said.