Businesses have begun to realize the significance of data governance and quality across different domains. Poor data quality destroys business value. However, although data quality improvement is the most discussed topic in the information management industry, companies often fail to implement effective strategies due to a lack of knowledge.  

Therefore, it is imperative to build a convincing data quality business case improvement, allowing you to implement and sustain data governance. A compelling business case is directly proportional to your data quality and governance strength. In today’s article, we will give you a step-by-step process to develop a data quality business case. 

Steps to Develop Business Cases 

Below are steps to develop data quality business case that help organization to improve data quality effectively. 

Step 1: Develop a Compelling Strategy  

The first step to develop data quality business cases is developing a compelling strategy. Creating a business case for improving data quality starts with developing a compelling strategy that must align with your economic or financial condition. The approach your company takes will determine the fate of your strategy.  

A business case for data quality will eliminate obsolete perceptions and implement a holistic strategy that enhances business processes and outcomes. Remember, it is not about what you do for improving data quality, but how you do it. Experts recommend focusing on the following elements.  

Acknowledge the Differences 

You must realize and understand the differences between making a data quality business case for improvement and a traditional project. Focus on differences that revolve around the non-conventional concepts, such as: 

  • Change management  
  • Business benefit  
  • Holistic impact  

When you understand these differences, you can develop and shape a better strategy within your organization. The purpose is to position your plan in the right direction. Otherwise, it will become another statistic and does nothing for your organization.  

Define the Program and Purpose  

Take your time and perform thorough research to know about how to improve data quality and how it will benefit your business. Remember, a simple definition of your data quality improvement program will go a long way and get everyone in your organization to work as a team.  

Getting everyone on the same page is an essential aspect of building a sophisticated strategy, the first step of creating a compelling business case. Bear in mind that this is even more important when data quality has different meanings to different people in your organization.  

That’s why we recommend fine-tuning this term’s characterization and its intent to align your managers, supervisors, and employees with your leadership. It is also an effective practice to clarify and document the purpose of your business case for data quality.  

Define Value Proposition 

Define the value proposition for your business case and determine whether it is for a single project or your entire organization. Although you can create a business case for a specific project, it is more effective when it impacts the whole data domain and enterprise.  

Step 2: Identify Value  

Business leaders, chief financial officers, and other crucial decision-makers weigh the data improvement program’s returns on investments (ROIs) in economic and tangible terms. Remember, this is one of the most significant fallacies about creating a data quality business case for improvement.  

Therefore, make sure you understand the program’s entire value and how it will benefit your business. Although the tangible benefit is crucial, a business case for data quality must measure tangible, realistic, and hard-to-measure benefits. The value of improving data quality focuses on five critical principles:  

  • Data operations  
  • Project management  
  • Company operations  
  • Organizational strategy  
  • Planning and development  

Step 3: Leverage Industry Sources 

Your business case for data quality must align with a specific objective and input from your analysts and data experts. You can benefit from research studies, books, surveys, articles, interviews, and blogs by industry specialists, allowing you to collect influential citations and add them to your data quality business case.  

In addition, leveraging industry resources allow you to mitigate that your stakeholders can effectively state their case. When you collect evidence-based information from research studies and employ it efficiently, you take one step forward toward building a reliable business case.  

Step 4: Perform a Data Assessment 

Performing a data assessment is a crucial step in developing a solid business case for improving data quality, enabling you to profile and analyze a subset of your business data. Using cutting-edge profiling tools and algorithms, your organization can measure data problems and their severity.  

At the same time, you can leverage the results supporting your data quality business case. Therefore, we recommend introducing tangible data metrics into your business case to streamline the entire process.  

Step 5: Determine Technology Requirements  

Technology is a constructive element in building a data quality business case and streamlining your data governance policies. Take your time and perform thorough research to identify the technology tools or requirements required for your business case. Remember, you must also analyze the expected investment.  

Identifying technology requirements can help your stakeholders understand the possibilities and impossibilities of the project. Some of the crucial technologies required for developing a business case for data quality you can use are:  

  • Data integration tools to access and move data between heterogeneous systems  
  • Modeling and simulation techniques for architects, designers, and developers  
  • Data quality management tools for process automation  
  • Data profiling for analysts and stewards to track, measure, and report on data outcomes  
  • Frameworks and workflows for exception management and removing data irregularities  
  • Unification and master data management (MDM) to synchronize data  
  • Presentation tools to facilitate consumers to access and present crucial data  

Step 6: Build Program Implementation Strategy  

Business owners often ask themselves: How do I implement this program? The answer is: building a program implementation strategy to develop a high-level concept definition to showcase your business case for improvement. Make sure you focus on the following elements.  

  • Organizational Structure: Define authority, roles, responsibilities, and accountability 
  • Business Alignment: The interoperability of your employees, departments, and committees. 
  • Accountability:  Define control strategies for data ownership and discipline  
  • Resource Requirements: Finding and aligning new resources with existing ones  
  • Rollout Plan: Develop a roadmap that includes goals, timelines, and milestones  

Step 7: Establish Funding Requirements 

You can’t develop a business case for improvement if you don’t have enough budget to fund the project. Financial support plays a crucial role in data governance success, allowing you to define the program value. Although the investment required varies from one organization to another, depending on their specific needs, we recommend allocating your finances to: 

  • Business case position  
  • Education and training  
  • Technology tools  
  • Third-party support 

Remember, you may focus on additional resource requirements, depending on your specific business case and data volume. Therefore, reorganize your departments, teams, and groups within your organization to carry out data improvement activities at no additional expenses to the company.  

Step 8: Document Everything  

Encapsulate your business case into a document and distribute it to key stakeholders within your organization. Make sure you create a concise, evidence-based, factual, practical, and easy-to-understand document. Your document for a business case for data quality improvement should include:  

  • Executive summary  
  • Purpose of the business case  
  • Data quality definition and concepts  
  • Data quality in your business and industry  
  • Overview of benefits, challenges, and risks  
  • The current state of your business case  
  • Value proposition 
  • Industry citations  
  • Data assessment results  
  • Example of past projects  
  • Technology and funding requirements 

Final Words  

Organizations that focus on developing a solid business case for data quality perform well on the market because they understand business requirements, insights, and best practices within the industry. In addition, they also understand the importance of data quality to avoid unwanted loss. The steps given above are a general overview of creating a compelling data quality business case for improvement. Until Next Time! 

In a nutshell, creating business case is crucial to all organizations to improve data quality. With many years experiencing in data solution industry, we know the pain of unwanted loss due to wrong data solutions for businesses. It led us to build a solution for all of you – SimpleMDG – a SAP BTP solution for Master Data Governance to help you solve your pain in data solution.  

More importantly, SimpleMDG has applied SCOUT Analytics – a 5th generation AI profit mining tool on SAP – to help build the most powerful SAP data governance business cases within 3-4 weeks during SimpleMDG implementation phase.  

Click here to request a Demo for SimpleMDG and get to know more about SCOUT.