CIOs and Data Scientists
Organizations — and their CIOs — need to support the ideal role of data scientists in order to improve their CX strategy.
A recent study from the McKinsey Global Institute suggests that data-driven organizations perform better on a wide range of metrics. They are 23 times more likely to acquire customers than non-data-driven companies, six times as likely to retain these customers, and, therefore 19 times as likely to be profitable.
These kind of results underline why so many companies are now striving to be data-driven organizations — 81 percent of companies believe that data should be at the heart of everything they do.
As data becomes a key driver of both business strategy and ROI, the number of data scientists within organizations is only going to grow. Leading retailers, for example, are planning to hire 50 percent more data scientists in the coming years to be able to more fully benefit from technologies like machine learning.
But there are challenges involved in attracting data scientists to your organization. Not only is there stiff competition for skilled talent, but many businesses don’t have the technology, processes, or culture that make it possible for any data scientist to do their best work for you or benefit from the experience of working in your enterprise.
Data scientists need the right resources to translate data into information and actionable business intelligence, especially for non-technical teams. To give a data scientist access to the data they need, in the format they need it, organizational transformation is necessary — and that starts with the vision and leadership of the CIO.
Reengineering your business
Benefiting from data and AI requires a fundamental shift in how businesses value, store, and share today’s most important intellectual property — data.
There’s a long history of attempting to retrofit new technologies onto old ways of working. Many of our job designs, workflows, control mechanisms, and organizational structures came of age in a different competitive environment with different technological requirements. They were geared toward efficiency and control, yet the watchwords of the new decade are innovation, speed, service, and quality.
Instead of embedding outdated processes into silicon and software, organizations need to obliterate them. What this means for CIOs is stronger alignment with other parts of the business, especially marketing and sales.
“Ultimately, the CIO needs to partner with the business to really understand what the business imperative is,” says Jim Rivera, head of product for the Adobe Experience Platform. “Anything that the CIO does has to be grounded in what is going to move the business forward. It’s not just about technology. Those are just tools to get a business problem done.”
How CIOs and data scientists can work together
Many data teams spend far too much time today preparing data and making it usable. However, no one in the C-suite is better equipped to empower data scientists than CIOs, since they control the data pipeline — and make the technology enablement decisions — that determine how successful a data scientist is at solving business problems while benefiting the customer experience.
“If you hire good data scientists, they know what algorithm to use. The challenge for them comes from not knowing what kind of data is available in the organization, how to get access to it, and then that the data itself is not necessarily clean — or labeled in a common language — and ready for the data scientist to put to use,” says Anil Kamath, vice president of technology at Adobe.
The first challenge — knowing what data is available and getting access to it — stems from the fact that many organizations currently have a patchwork of technology stacks. Each department is filled with different point solutions that aren’t interoperable and further perpetuate data silos. CIOs have been focused on optimizing the different technology stacks for each function, and they’ve done this well. Shifting focus to an overall business optimization strategy represents a mindset shift for the entire organization.
CIOs play a critical role in supporting the development of a data-driven decision-making culture, and ensuring that data from across the enterprise is brought together for the good of the organization as a whole. Even more importantly, this consolidation benefits every customer as an individual — for their brand experience, privacy, and security.
“In many cases, it’s been the realm of very large companies that have a lot of assets to be able to build out the technology infrastructure to solve their unique business problems, but that’s changing. The tool sets are getting better, and the platforms are getting better,” Jim says.
“Today, they can take advantage of platforms that will allow them to focus on solving business problems and not having to try to stitch together and build the infrastructure themselves,” he adds.
In the Experience Era, that infrastructure should include an AI and machine learning-driven platform that standardizes your company’s data into one common language and that can democratize data collection and analysis, allowing data scientists and non-technical teams alike to more easily derive insights from data.
A platform that layers on intelligent services that can solve specific problems in the marketing and advertising domain also can help your organization get more out of its structured and unstructured data, and free data scientists to focus on work that drives more impact for the business.
Anil says having these tools — and people equipped to use them — may enable companies to reengineer their workflows and tasks by leveraging data science to make better, more relevant, real-time decisions. AI and machine learning can take companies from a backward-looking, descriptive use of their data to a more forward-looking, prescriptive approach that enables autonomous decision-making, allowing them to better meet their customers wherever they are — in time or space.
As CIOs assume a key role in transforming the availability and value of enterprise data, using these technologies will be critical for IT teams, and data scientists in particular, to help their companies improve customer engagement, retention, and loyalty.
Transforming data scientists into change-makers
As technology and the understanding of the power of customer experience have evolved, so have the talents and skills of the people who can find and exploit the data that feeds it.
Data is now the main currency of the experience economy, and companies will need to undergo both technological and cultural transformations to more skillfully use their enterprise data to improve their customer relationships.
Data scientists are now critical players in driving every company’s customer experience strategy, and CIOs can empower them with resources that will increase their value and overall business impact, Anil says.
“You need to think of data scientists as not just experts in using algorithms or providing insights,” he says, “but in terms of how can they be changemakers in their organization.”