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A Data Management Approach that Supports Data-Driven Decision Making

Author: Bankim Sheth | | September 27, 2022


 

Data-driven decision making is proving itself to be invaluable in almost every business vertical. The challenge is identifying the right data management/analytics approach that will allow your business to achieve successful data-driven decision making.

The Current State of Data-Driven Decision Making

S&P Global Market Intelligence used the results of their annual Voice of the Enterprise survey to gather some information about data-driven decision making. Survey respondents answered some of the questions many IT and business leaders are asking.

How many of your strategic decisions are data-driven today?

The answers were organized in four categories:

  • 26% of respondents indicated “Nearly All”
  • 44% of respondents indicated “Most”
  • 21% of respondents indicated “Some”
  • 9% of respondents indicated “Few”

Looking 12 months in the future, how important will data be in your decision making?

90% of respondents said data would be more important, 9% said there would be no change, and 1% said data would be less important.

Based on those results, 70% of your competitors are using data to make most or nearly all their strategic decisions and future planning. And, the vast majority of respondents said that data will be even more important to their decision making in the future. Therefore, if your business isn’t putting focus on data-driven decision making and future planning, you’ll be behind the curve when it comes to maintaining or increasing your competitive edge.

S&P also asked respondents about the most significant benefits of data-driven decision making, and these were the results. Respondents could choose more than one.

  • Increasing business agility: 56%
  • Streamlining and automating business processes: 49%
  • Improving sales: 44%
  • Elevating customer service: 43%
  • Empowering and aligning company decision makers: 41%
  • Improving their competitive advantage: 40%
  • Simplifying regulatory compliance: 40%
  • Reducing risks: 39%
  • Reducing costs: 36%

 
Looking at that list of benefits, you can see why so many businesses are focusing on accelerating data-driven decision making.

The respondents also recognized that there are challenges when it comes to supporting data-driven decision making. In fact:
 

  • 34% of respondents noted that data security is a challenge
  • 29% indicated that data integration was a challenge
  • 25% cited the ability to access and prepare data
  • 19% said it was difficult to build and maintain their data infrastructure
  •  
    These challenges revolve around the data management approach that the respondents are using, illustrating that it’s critical to get data management right.

    Developing a Data Management Strategy to Support Data-Driven Decision Making

    Data management is the vehicle to achieving a data-driven decision-making organization. Data management is the process you use to gather, secure, organize, maintain, govern, and analyze data. But it’s not the only ingredient you need for an effective data management strategy.

    You also need to address the topic of data governance to ensure that everyone in the organization who is involved in data management is using consistent rules for access, collection, storage, and analysis. Finally, you must address data quality. You can have an amazing data management strategy, but if the data you start with isn’t accurate, you could be making decisions based on faulty information.

    The Role of Data Fabric and Data Mesh

    Data fabric and data mesh are two modern frameworks you can use to elevate your data management organization. These aren’t discrete technologies, rather they are design concepts that use a variety of technologies to meet your data requirements.

    Data fabric describes a concept of an integrated layer of data and processes that connect them. It provides a global view of your business’ performance and eliminates data silos, and gives you the ability to standardize this critical data.

    Data mesh uses a concept that gives responsibility for data management to the business domains in your organization. Various business domains are responsible for preparing their data to be used in business intelligence applications. It creates a self-service platform that allows users to access real-time data for immediate decision making.

    Data fabric and data mesh can be used stand-alone or in combination to meet your needs. You may determine that you need one or the other, or both working in concert depending on your goals and objectives.

    The Challenges You’ll Face

    Elevating your data management capabilities may be necessary to help your business improve its competitive edge and growth. But, there are challenges as the research referenced earlier indicate.

    You’ll need to consider your existing systems, manage dependencies between infrastructure services, create new data models, integrate with external systems, to name a few specifics. Unfortunately, many businesses don’t have the internal expertise to address all these challenges. Data management is probably not among your company’s core competencies. In that situation, you need to partner with an experienced firm like Datavail to ensure that your projects and strategies are successful.

    Datavail can provide experts in all the arenas you’ll need to address as you create new data management infrastructures, including:

    • Business intelligence and analytics
    • Data governance strategies
    • DataOps services
    • Data integration
    • Data warehouse and analytics
    • Data lakes solutions
    • Cloud solutions
    • Managed services

     
    To learn more about data fabric, data mesh, and how we can assist you in planning and implementing these types of solutions, download our white paper, “What Can Data Fabric and Data Mesh Do for Your Data Management Approach?” Or, contact a Datavail expert to discuss your specific requirements and challenges.

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