Without data, businesses wouldn’t have much to work with when making informed decisions. Data by itself, though, isn’t enough for business leaders to rely on when they’re driving growth; a gigantic collection of data isn’t worth nearly as much as a data strategy defining how you use and manage your data.

Without a solid data strategy, CIOs would be making uninformed calls on how to use and manage their data. From the fundamentals of data governance to sophisticated techniques to analyze data, progress in data strategy formation goes a long way toward improving a business’s functions. 

To ensure that CIOs properly use and manage the vast collections of data at their fingertips, we’ll discuss the four must-know data strategy priorities for CIOs.

1. Democratize Your Data

First, CIOs need to do more these days than just give users access to analytics and data. In today’s hyperconnected world, more jobs than ever require either manual or automatic interpretation of data. And although not all tasks require that a human interprets data, providing employees access to more tools allows them to explore data, manipulate it, and even become more data-literate and competent independent of help from data specialists. 

To ensure a greater number of employees can do more than just menial reporting, CIOs must develop a data strategy that prioritizes accessibility and transparency to ensure employees’ expectations – and sometimes demands – for greater data access are met. This is especially important as more workplaces begin to have more data-literate employees who also expect data democratization.

2. Orchestrate Your Data

We’ve arrived at a crossroads when it comes to technological innovation. Whereas organizations with siloed data and more than one on-premises location for data storage were initially leading the digitization race, they now find themselves lagging behind, searching for a way to combine their disparate sources of data and centrally organize their information.

With the help of a centralized data architecture, businesses can automate data-driven decisions and support tools that drive data-driven decision-making. Data orchestration makes it easy to centralize data, execute insightful analyses, and ensure security and privacy, which is particularly useful for banking entities that need to ensure money is kept safe from fraud. 

Data orchestration also standardizes the data it collects from disparate sources. When it’s from silos to a centralized data system, it allows organizations to tackle various critical problems.

Among these critical issues is compliance with data privacy laws, which affects certain industries significantly. For example, the health care industry’s medical clinics will often rely on direct patient communication software to help ensure the confidentiality of patient data while also providing actionable data and analytics to help with things like last-minute appointment scheduling. Other issues that data orchestration can help with include the removal of data bottlenecks and organization-wide enforcement of data governance. 

3. Create a Drive-to-Market Data Strategy

Most businesses have the knowledge and infrastructure to manage data that relates to business growth. What most businesses don’t have, however, is a data strategy that is designed to respond to drivers in the market. The data platforms that businesses use should be as flexible as their data strategy to keep up with quickly changing business conditions and priorities.

CIOs must ensure that they apply this level of flexibility to two aspects of their strategy: data organization and data management. Adaptability, as it relates to data management, is chiefly associated with tools organizations use to provision data. These tools should be able to support future additions of data and consumption-layer applications. 

CIOs would do well to remember that data organization must remain inherently flexible too. Sets of data domains that directly relate to an organization should be identified, and a data governance team should be established around them. 

A data domain’s relevance changes in response to an organization’s evolving market strategies. There, the governance and organization of data should aim to estimate which data sets will become important down the road, and they should be able to identify how a system will respond to the changes.

4. Double Down on Risk Management

As of 2023, data governance has become more than just another way to refer to data compliance. Data governance relates to the use of data to support and build on existing business strategies. CIOs need a formalized structure for their data governance to make the most of the limited resources at their disposal. This formalized structure should include data domains defined not on the physical locations of data but actual business topics (“customer,” for example). 

By avoiding defining their data domains based on where data is physically located, CIOs can more efficiently keep track of their data while ensuring that they’re complying with regulations and industry mandates and standards. CIOs and their teams must establish a complete understanding of risk management, especially as data continues to become more valuable.

For instance, a customer’s contact details or PII should always be stored in retrievable forms that cannot be used for illicit or unauthorized reasons. Additionally, each country has its own set of government regulations that outline guidelines when it comes to storing and handling sensitive customer information.

CIOs will want to collaborate closely with their compliance and legal teams to manage risks that directly relate to valuable data; doing so will help CIOs ensure that they have a data engineering strategy that aligns with their organization’s risk management strategy.

Conclusion

If you’re a business leader still trying to iron out some backward approach that begins with your products but ends with your customers’ requirements, you must go back to the drawing board and rethink your whole MO. Your focus must begin with your customers’ requirements so that you end up with an approach that’s outside-in. Shifting your focus to an outside-in approach that prioritizes customer requirements and proper data management is crucial for CIOs who want to help their organizations gain a competitive edge in the market.