It’s a new year, but we’re still facing many of the same challenges as in 2022. Businesses are preparing for greater economic uncertainty, often looking for creative ways to keep costs low while still meeting goals for the year. By becoming data-driven and using data intelligence to fuel business decisions, leaders can confidently make key decisions and move their business in the right direction.

In fact, according to a recent IDC report, companies that used data intelligence to fuel business decisions saw a 484% three-year ROI and a total average of $9.1 million in annual benefits. Data intelligence also increased revenue and productivity while reducing costs. For example, taking a data-first approach can help data analytics teams locate data and reports 57% quicker, increasing productivity by 13%. 

Below are recommendations and predictions for what’s ahead this year as organizations transform data processes and embrace data-driven insights. 

Engage All Areas of the Business 

Organizations want to be data-driven but are often overwhelmed by the volume of data coming in and the growing complexity of the data landscape. Whether the data is in the cloud, on prem, or in different organizational silos, getting full visibility is a challenge. Without full visibility of data, you can’t start to manage, govern, or make data easier to find across the organization. Additionally, many teams lack a common understanding of data, which often leads to confusion – one user thinks the data means one thing, while the other thinks it means something else. 

For an organization to truly become data-driven, leaders must recognize that it can’t just be IT or the data office that is focused on solving these challenges. All areas of the business need to be data-driven, and therefore all areas of the business need to be engaged in data processes.

Start with getting recognition and buy-in from key stakeholders. These stakeholders need to recognize that these challenges should be addressed, agree to participate in developing new processes, and commit the time and resources needed to support these efforts.

Data Mesh Drives That Business Engagement

Data mesh is all about maximizing the value that organizations can reap from their data. Centralized Data Management practices often cause silos, so data mesh’s principles on decentralized command and control of data out toward business domains breaks down those silos. Further, applying “product thinking” to data is where the value proposition lies – every data product needs a business case, a strategy, and attention toward ROI, all things that inherently matter to lines of business.

Boost Data Literacy for a Competitive Edge

As organizations adopt this approach of distributed Data Management and product thinking, we will start to see a greater emphasis on data literacy throughout the business. Data literacy, or the ability to read, write, and communicate with data in context, is needed to derive insights from data, but it will also be an increasingly important competitive advantage. Genuine data literacy is applying those reading and writing skills toward generating something valuable from data.

Any company that can truly drive data literacy and empower more people to make key decisions based on data is significantly ahead of everyone else. Data literacy is a cultural shift, and it takes time to build a strong foundation. Chief data officers and data leaders should be leading the charge on data literacy through continuous education and training.

Intentionality Regarding Data’s Value

Maximizing value from data means measuring it. Data monetization strategy led by data officers will help the business quantify the value of those data products in financial terms – costs of technology and personnel to create and support data products, as well as the return on that investment in the form of increased organizational efficiency, enhanced product and service offerings, or even the sale of commercial data products to the market.  

Data Observability Is on the Agenda for the C-Suite 

Data observability is rapidly becoming a key priority. In 2023 and beyond, the scope of data observability will expand as companies begin to take a closer look at areas such as data privacy and security through the lens of data observability. Across the board, data observability will become key for C-level decision making as it expands beyond data quality into other facets of the business as well.

2023 will be the year many companies aim to be more data-driven. We will see companies commit to new data processes, prioritize data literacy efforts, and put more emphasis on continuous data quality and observability to succeed.