Why Taking Data Management to the Next Level is Easier than You Think

At a glance, data issues can seem like an insurmountable challenge for most companies. Data is larger and more complex than ever before. Data is also more unstructured and disparate, spread across legacy systems. These create silos that seemingly hinder the effective use of data in any capacity. 

Adding fuel to the fire, data teams are often relied on to gain actionable insights, deliver better customer/user/patient journeys, and help companies find new ways to do or make more, with less.  

As a result, companies are perpetually spending enormous time and money lifting and shifting outdated data in the hopes of achieving business goals. But it doesn’t have to be so hard or ineffective. There is a lot that IT leaders can do to drive more efficient data management without having to undergo a costly “rip and replace.”

These issues are some of the many reasons why fewer than half of data and analytics (D&A) leaders reported that their teams are effective in providing value to their organization, according to Gartner. 

The Gartner survey was conducted online from September through November 2022 among 566 D&A leaders globally; the findings underscore how Chief Data and Analytics Officers (CDAOs) need to drive business value by taking small, measurable steps. Specifically, CDAOs “need to focus on presence, persistence, and performance to succeed in their role and deliver measurable business results,” said Donna Medeiros, senior director analyst at Gartner.

“D&A [teams are] in the business of driving stakeholder value,” Medeiros said. “The most successful CDAOs are outperforming their peers by projecting an executive presence and building an agile and strategic D&A function that shapes data-driven business performance and operational excellence.”

The challenge, however, is often how to start and where to go from there for most CDAOs. 

Data Management is the Solution to Complex Data

The journey to mature data management has to start with governance – the framework, policies, and procedures for managing and protecting data assets. This approach to solving data challenges entails simplifying data management, including how to build processes and operate data. 

Unless you understand and articulate the governance structure the organization intends to achieve, it is unlikely that making changes to data structures, access requirements, rules for using the data, and a whole host of other elements that need to be revised, will yield the desired results. The lack of governance is what most businesses get wrong when seeking to adequately match their data management processes to their real-world business requirements. 

Governance involves establishing roles, responsibilities, and decision-making processes related to data management, including data quality, privacy, security, and compliance. When governance is not formally defined, organizations run numerous risks, including the misalignment of data usage and the organization’s initiatives, increased compliance issues and security risks, limited access to data, and low-quality data. These all lead to wasted time, effort, and money.

According to a recent eBook (enter link) on Data Management by Ippon Technologies, “The opportunities created by establishing a strong governance structure are manifold. Creating and observing them creates alignment with the organization’s strategy and goals; they establish clear roles and responsibilities enterprise-wide; and they protect both valuable organizational data and the organization’s reputation.” 

At a glance, getting data issues sorted out seems like an insurmountable challenge for most companies, but by taking simple steps such as planning for data governance and taking iterative steps to implement it, organizations can make strides in addressing the complexity of modern data management. 

For more information on creating the best data governance for your organization, visit https://us.ippon.tech/ or download our latest eBook "The Future of Data Management" here.