The ‘data-driven’ chief data officer: 7 steps to success

Businesses understand that their data capabilities — the data they possess and the way they utilize it — can provide a competitive edge and help them in expanding market share and displacing competitors in their sector. Thus, data capabilities are no longer necessary just for their success. In fact, they’re crucial for their existence. Moreover, leveraging data the right way provides firepower for growth. The thing is, for a business to ensure that all kinds of data deliver value requires enterprise-wide governance and organization. And, that is the job of a chief data officer.

This is a relatively new profile, originally meant to oversee data quality, governance, and regulatory issues, but now expanding to the frontlines of the analytics revolution. A chief data officer can show data-driven organizations how to boost growth and revenue in the following ways:

1. Clearly explain your business data and analytics strategy

chief data officer

A chief data officer must first devise a comprehensive charter, showcasing a simple vision of what a data-driven company looks like in reality, along with a mission statement of what the business does as well as a narrative that makes analytics and data real for people without a quantitative or data management background.

Usually a part of analytics and data business case, the charter must highlight practical business outcomes to provide a better understanding of the scope, focus, and intent. The trick is to lead by example and then with examples.

2. Devise and implement a bimodal approach

To fulfill this balancing act, a bimodal approach is needed. And, a bimodal approach involves managing two distinct modes of IT delivery, one of which is focused on agility while the other is on stability. Careful resource management, as well as the ability to serve new and classic requirements, are important for maintaining balance within the bimodal environment. It is necessary for the chief data officer to regularly revisit the team structure for supporting growth and maintaining agendas.

3. Delineate your analytics and data strategy and roadmap

data capabilities
Flickr / Daniel X. O’Neil

It is never easy when an organization decides to make the switch from business intelligence to analytics. However, this shift in focus can be made smoother by modernizing the existing business intelligence roadmap and strategy as well as supporting the progress of data science and analytics capabilities.

It is also vital for the business to align with the information management roadmap and strategy so that an integrated plan might be formed — one that carefully monitors signs of interdependence across major infrastructure efforts, especially while the architecture (this is not the same as the architect in the amazing movie “Inception”) changes from the traditional data warehousing to a more logical virtualized environment.

4. Employ quarterly reviews to liven up your strategy

Make it a point to review the critical path, strategy, and roadmap with major stakeholders and shareholders each quarter. While you’re conducting an inventory update on a regular basis, try to maximize collective resources throughout the community, even as you update the inventory with a similar frequency. You can also share the successes on a regular basis by keeping the strategy “live” at all times.

5. Make the chief data officer the ‘center for analytics’

your analytics and data strategy

When a business hires a chief data officer, they expect him or her to become the go-to individual for all analytics and data-related endeavors. For this purpose, it is necessary to work out the issues within the immediate team, or increase awareness of and broadcast what goes on throughout the analytics and data community.

This means facilitating and endorsing a self-service environment — one that fits the needs of a wide range of data scientists and analysts throughout every sector of business. Once you succeed in this process, it expands the impact and decreases the load on the central team.

6. Form an alliance between your analytics and data partners and colleagues

You might be the chief data officer of the company, but not every infrastructure, analytics, or data management coverage falls within your purview or direct charter. In such circumstances, you need to interlock closely with IT and other influential personnel throughout the business.

One more vital reason for forming such an alliance is how, as the analytics charter evolves, it starts requiring and accommodating a greater data ecosystem, a large chunk of which is sourced externally from open data sources, emerging data brokers, and social data sources.

So, instead of ridding the company of data analysts, exploit their knowledge. The new generation of products might not be as complicated as their predecessors, but they can still cause confusion. But when you have a data analyst in your corner, you can ask them to set up the analytics solution in a way that makes your life easier.

At the same time, use the data analysts for more strategic tasks, such as defining shared metrics and adding new sources. Do not waste their talents on building cubes (no this does not have anything to do with the fantastic rapper Ice Cube), adding new columns, or altering chart colors.

7. Find out about your ‘costs’

Hiring a CDO means additional expenses for a business; you just need to show them that you’re worth every cent being invested in you. Find out how much you’ve been spending on data analytics talent. You might be able to save a lot of money and time if you find a product that is simpler to use.

Once that’s done, put it on your agenda to discover how exactly the pricing of your analytics tools changes when new users, CPUs, devices, data volumes, and cores are added. There are vendors who charge you incrementally each time to try to add a user or switch the current IT configuration. And if you’re not careful, things may spiral out of hand. That’s why it’s best to consider predictive licensing models that do not charge you anything that is unnecessary for adoption.

A CDO must always be up to the task of using a ready set of tactics to deflect the winds of change blowing through the business. And in the process, they must help data-driven businesses reach their potential and grow.

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