How Chief Data Officers Overcome Key Challenges

The role of a Chief Data Officer (CDO) is relatively new and hence, laden with many new challenges. But knowing these issues beforehand can help you be equipped to solve them. Whether it is aligning with the business strategy or steering people towards a change, the key is to understand business pain points and establish solid, informed strategies. 

The Chief Data Officer role is growing more challenging as the volume, velocity and variety of data increases. Add to this the burgeoning need to focus company growth strategies on data-driven initiatives, and it’s not surprising that the obstacles presented to CDOs are becoming increasingly tough to navigate.

The critical challenge in front of the CDO is to formulate various data rules & procedures so that users address the whole initiative with competency and enthusiasm rather than burden.

This article will cover the three significant challenges facing CDOs and provide actionable solutions to overcome them.

CDOs struggle to align data strategy with business objectives

Problem

I talked to a CDO friend about their business strategy, what tech stack they were using, and how they were trying to get data into a unified platform. When I asked what use cases they were trying to solve, he said they would figure it out after the tech stack was ready. Do you see the problem with that approach?

It often happens that CDOs, or data governance heads think about the business problems after the tech stack is ready. Even without a business case, they succeed in securing funding by creating a sense of urgency that if they don’t invest in technology, they will be left behind in the innovation curve. But that’s not a good start. Why? Because if data objectives are not clearly defined and aligned with the business, you are a hammer looking for a nail.

Solution

Why is it happening? CDOs are often promoted from a data analytics background. Hence, they have phenomenal technological expertis, but a lack of business acumen. They should train themselves – take a different role for some time to gather business acumen. On the other hand, if a CDO is from the business side, they know the problem to be solved but do not have the technical skills to execute the data initiative.

For example, if a business decides to focus its core strategy on mergers and acquisitions, analytics is unlikely to be the primary use case for company data. Instead, the focus will likely be on integration and data quality.

Alternatively, if an organization decides that acquiring more customers is the focus of its strategy, then data around consumer behavior and market trends will be most helpful. Or perhaps a company wants to increase its operational efficiency. In that case, data analysis could play a massive role in providing the information required to streamline operations.

CDOs mainly try to solve problems that they know how to solve

Problem

In the past, the CDOs have mostly come across issues like getting all data in one place, query performance, etc. So, they see new data warehousing technologies like Snowflake or Databricks and get excited about how quickly the queries run. But they are oblivious of the snags which will arise next.

Solution

After getting all your data in one place, issues will arise in these areas:

  • Compliance and confidential data issues after data ingestion is done
  • Collect tribal knowledge about which data to use since there will be lots of data, especially duplicate data
  • A need for a governance ecosystem
  • Collaboration between business and IT for a new business use case
  • Deal with the challenges of data quality and trust when the data warehouse goes live i.e., when the users start accessing data in the warehouse

Knowing about the compliance and governance issues beforehand can help you get equipped to solve them.

CDOs find it challenging to steer change management

Problem

To succeed as a data-driven organization, a company must look beyond simply rolling out the technologies and procedures to support this transformation. It is essential that the company transitions into supporting a culture of data-driven innovation too.

Look at it this way. If you owned a restaurant and equipped your kitchen with the latest gadgets, and provided your staff with innovative menu ideas, would it be able to contend with the most cutting-edge competitors? Probably not.

Along with these provisions, you’d have to change the habits of your kitchen staff. Encourage them or even hold their hand and make them try the inspiring recipes and technologies available. And give them a reason to innovate.

Solution

First, let’s discuss this definitive approach to change management. Here you will:

  • Clearly define objectives
  • Clearly define the use cases
  • State the ROI
  • Have transparent communication from the top to the lowest rung
  • Make the team according to the objectives, not work as per the existing team, e.g., you have good developers, but you need a good program manager to run the initiative.

When people have clarity about a change, they are more willing to participate in bringing it. Then, there are change management coaches you can bring in.

If you want to transform your organization, you need to transform the individuals that work within it.

Many users are immune to change. It’s much easier and less frightening to stick with what you know and continue practicing the tried and tested procedures that work.

If you want to introduce a data-driven culture, you need to work directly with individuals. One of the best strategies to achieve this is to run workshops. Start with the most senior executives in your organization and work your way down.

In these training sessions, you must explicitly show how data can transform a company from the top-down. Once you have your senior business leaders on board, this newfound approval should trickle down. However, it might be essential to target any resistant teams and departments too. If possible, create a web-based forum where business users can see the progress of data initiatives. This ongoing monitoring should encourage them to do more with data as they see how much it contributes to the growth of their organization.

Wrap Up

Although they aren’t the only ones, the challenges we’ve highlighted in this blog are the most pressing for the modern CDO. Every CDO will face unique problems. Yet, the key to overcoming most stumbling blocks is to establish solid, informed strategies.

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Shilpi Agarwal

Shilpi Agarwal

Shilpi Agarwal is Director, Data Governance Outreach at OvalEdge. She has been directing digital content for OvalEdge, an end-to-end data governance tool since its inception. Her passion is to listen closely to data users and their pain points and develop content accordingly. She has done her MBA from Georgia State University.

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