Getting Started in Your Data Management Journey

The four questions you should ask before launching a data management initiative.

Data is the backbone of any modern organization. However, the quickly accelerating pace of data creation reveals the limitations of existing data management strategies and architectures. By 2025, we expect 180 zettabytes of data in the global datasphere with a compound annual growth rate of 19.2%¹. Wrap your brain around that concept. Modern data management is no longer optional. It’s essential for maintaining security and compliance while accessing, integrating, cleansing, governing, storing, and preparing data.

Shifts in the technology landscape indicate many companies are contending with data management modernization for the first time. According to Concord’s Data Engineering Director, Jeff Rogers, the digital transformation trend and holistic approaches to data management will continue into the foreseeable future.

For those just getting started, what are the first steps a business should focus on to create the foundation for a successful data management journey? Jeff suggests that organizations evaluate and build a roadmap for approaching data management modernization. Answering the following questions will help guide you in making this assessment:

1. What objectives is your organization trying to achieve?
   

   This initial stage is critical because, as Jeff shares, “if the technology can’t directly support the business objectives, it’s not going to work.” Defining the objectives of the data management modernization journey will crystalize the overall goals and make them measurable.

2. What does your company do, and what does that look like at its highest level?
   

   This question highlights the organization’s niche and direct strategies, which help enable peak performance.

3. How do you expect the technological ecosystem will evolve to support the vision and direction identified in the first two questions?
   

   This question requires a person to consider the understated elements needed to achieve successful data management modernization.

4. What is your company’s capability maturity level?
   

   It’s helpful to assess the organization’s current technological capabilities, processes, and performance using a digital maturity scale like the Capability Maturity Model Integration (CMMI).

CMMI is a model that streamlines process improvement and encourages productive behavior that decreases software, product, and service development risk. The CMMI model breaks down organizational maturity into six levels from 0 to 5. Factors like a company’s size or reputation do not correlate with maturity. The CMMI maturity levels are detailed below².

• Maturity Level 0—Incomplete: Goals are not established, processes are partially formed or do not meet the organizational needs, work may or may not get completed.
• Maturity Level 1—Initial: Processes are unpredictable, poorly controlled, and reactive. Work gets completed, but it’s often over budget and delayed.
• Maturity Level 2—Managed: Processes are still often reactive but are characterized for projects. A degree of project management has been achieved that provides planned, performed, measured, and controlled projects.
• Maturity Level 3—Defined: Processes are proactive and characterized by the organization. There is a set of organization-wide standards that provide guidance across projects, programs, and portfolios. Businesses can understand lingering issues, how to address them, and what the goal is for improvement.
• Maturity Level 4—Quantitatively managed: Processes are measured, controlled, and proactive. The business can use quantitative data to forecast predictable processes that align with stakeholder needs and can harness data-driven insights to mitigate risk from process deficiencies.
• Maturity Level 5—Optimizing: Processes are stable and flexible, allowing the organization to focus on continuous process improvement. Businesses in this final stage are primed for maximal agility and innovation due to a stable, predictable environment.

Organizations at Level 4 or Level 5 are considered high maturity. Within these stages, companies consistently evolve, adapt, and grow to meet the needs of stakeholders and customers. Organizations early in their data management journey will likely exist somewhere between Level 0 and Level 3. Ascending to higher levels is a gradual and iterative process. As Jeff advises, “If you’re less mature, it’s really hard to scale your business - period.”

Graduating between maturity levels is especially difficult without the solid foundation of a mature system. Many early-stage companies are still reliant on manual processes or attempting data integration for the first time. Jeff recommends an “alongside approach” to introduce data management modernization to a business. In this method, a trusted partner helps business teams get started with the tools required to deliver on projects. This iterative and guided strategy adds value by streamlining processes and provides the support needed to make an impact right away. 

Universal solutions for modernizing data management do not exist. Every company faces challenges that require a tailored approach. By starting with an appraisal and building a roadmap to meet the organization’s goals, companies can transition from the passenger seat to controlling the steering wheel in their pursuits for more modern data management.