Data is fast becoming the essential backbone of any organization, and with top tech talent running scarce, chief data officers (CDOs) need to make sure they have a robust plan in place to provide avenues for young data specialists to come in, learn to apply their skills, and unlock data benefits for the business.

To support a top-notch team in this era of digital transformation, CDOs must also ensure they’re providing opportunities for growth and personal development within the company, a particularly important goal in an age of high turnover.

From the perspective of Josh Drew, regional director at Robert Half, a talent solutions company, a successful data department involves data analysts and data scientists, and data engineers who get multiple systems communicating with each other, as well as extract and analyze data.

“You also need people versed in data storage, as well as extraction of data in analytics, and then you have data privacy, which means there’s a security component as well,” he said. “Within the data space, these people would represent the core of a department.”

Drew pointed out that as data analytics moves into a central role within an organization, a CDO has to look beyond the anticipated headcount for today and start planning for what the future needs will look like based on the direction and the trajectory of the business.

“The first step is fully understanding what you currently have,” he said. “Once you have a good grasp of the existing team or the model you’re trying to build out, you’re in the position to determine what you need from a specific headcount.”

For CDOs coming into a new organization, Drew added, that could mean reducing headcount and making the team leaner or more efficient by introducing automation technologies to free up resources.

Anand Pandya, global head of financial services for Hakkoda and former CDO for Informa Financial Intelligence subsidiary Curinos, the twist on a CDO’s team is that it’s less about technological data skills and more about understanding the business application of data.

By looking for “business analysts”, “data analysts” and “systems analysts”, a CDO can build a top-tier team of talent that understands both how to research, analyze, and work with data while applying it to business cases, strategic alignment and process workflow.

“More often than not, this talent pool is looking to find a career path that supports both sides of the skills, so providing a clear path forward to grow along data stewardship and governance or data science and innovation allows a resource to see a future and purpose to stay and grow,” he said. “Look internally for hungry analysts wanting to impact the firm. Look externally for those with 2-3 years of practical experience ready to take the next step forward.”

Pandya explained that like most newly minted departments, the core focus of the business may not be on the CDO, and therefore the investment cases may not be as readily apparent as they are for the CTO, CRO, COO or CFO.

“Acquired talent may need to wear multiple hats, be prepared to learn quickly, and spend time across the business organization listening and identifying quick wins,” he said. “Though this can be exciting for some, it can be frustrating for others.”

Therefore, it’s critical for a CDO to be constantly aware of the CDO charter and vision and ensure that the team knows what they’re doing aligns to said charter.

Pandya said developing talent in the CDO office isn’t about certifications and “projects”, it’s about alignment to a strategy and understanding that progress isn’t always seen by those making it.

“With the more technical aspects of data science, it’s clarity in purpose,” he said. “Nothing will frustrate a data scientist more than being told to ‘just explore data’. The CDO must be able to provide guidance on problems to be solved. Continue to give the team the proverbial Rubix cube to solve, and they’ll feel challenged and fulfilled.”

From the perspective of Caroline Carruthers, co-founder of global data consultancy Carruthers and Jackson, being honest about the data maturity level of the organization is key to ensuring you get the right balance of team members.

“If you are incredibly data immature as an organization, the focus as you build the team should be heavier on the governance side, because you need to make sure you up the quality to a reasonable level to be able to do something with it,” she said. “If you are highly mature, then you’re probably going to be much heavier on the data product management side, the data analytics side, because you’ve got something to really drive forward.”

She added one key thing a lot of data people share is that they’re problem solvers, where the interest in the data is derived from their ability to see patterns in the data that help solve big problems.

That means for the CDO, its important to sell the ideal to potential hires that they can make a difference solving the challenges the organization faces, and how those goals can be achieved.

“That attracts a lot of data people,” she said. “The majority of time businesses are trying to sell the whole, ‘We’ve got this covered, it’s fine.’ This isn’t the way to attract these people more and more. A lot of data people are attracted by solving issues. Not many organizations are honest enough about that kind of stuff. But the truth is, when it comes to data, it’s that type of honesty that would attract somebody.”