In today’s dynamic business landscape, you may have realized that data plays a crucial role in your organization’s success. But what is often underestimated is the inherent value of effective data management within your business cases.

In this article, industry veterans Fredrik Ekman, management consultant and data specialist at Valcon, and Ida Eriksdotter, Valcon’s esteemed master data management lead, draw upon their extensive experience in data and BI projects to illuminate the significant, yet often unnoticed, role that effective data management can play in achieving your business objectives.

The Crucial Role of Data Management in Business

The role of data management in business has never been more significant, especially when considering the increasing focus on digital transformation and other business initiatives. In fact, the success of these initiatives is often directly linked to the quality and management of data within an organization.

The grim reality is that most large-scale technology projects fail, with Gartner reporting that a staggering 70-80% of all BI projects don’t succeed. The story is even more concerning when we examine data quality, with Gartner also highlighting that 40% of business initiatives are unsuccessful due to poor data quality.

These failures come at an enormous cost, not just in financial terms but also in the wasted potential for enhanced decision-making and strategic advancements. McKinsey reports that only 30% of digital transformation projects improve corporate performance, indicating that the remaining 70% fail to deliver any measurable ROI.

So, what’s driving this high failure rate? We’ve identified four main reasons:

1. A lack of necessary talent within organizations
2. Insufficient executive support for large technology projects
3. Corporate cultures that are subtly resistant to technology, despite pro-tech rhetoric
4. Poor data quality and existing infrastructure that doesn’t align with business goals

BI, a vital component in today’s data-driven business landscape, has been in the top 10 issues for CIOs for over a decade. Patrick Meehan, president and research director in Gartner’s CIO Research group, points out that “BI is a moving target and it changes every year as tools become more mature… the finishing line keeps moving forward.”

Often, businesses view BI as a purely technical challenge requiring specific package solutions, which leads to a disconnection between IT and business needs. This misalignment, coupled with poor communication and the failure to address the real needs of the business, results in most BI projects falling short of their goals.

MDM (Master Data Management) initiatives present a solution to this prevalent issue. These initiatives, which focus on the management of an organization’s critical data, can drive instant value and serve as a concrete proof of concept when applied to specific areas. However, to optimize the benefits of MDM, businesses often require both short-term and long-term solutions, highlighting the need for strategic planning and implementation in data management.

Making the Business Case for Data Management

The business case for data management lies in its potential to create considerable ROI, by increasing revenue, improving operational efficiency, enhancing the customer experience, and ensuring compliance and risk mitigation. However, these benefits are often not readily apparent to business leaders, necessitating clear and compelling demonstrations of the value that effective data management can bring.

Communicating the Value to Business Leaders

To convey the value of data management, it’s crucial to ask and answer the following questions:

1. How much will the revenue increase, and in what way is data management enabling that?
2. How can data management improve efficiency with data processes, and what cost benefits can we expect?
3. How will it deliver a better customer experience, and what specific benefits can our organizations expect to see as a result?
4. How will it help our organization ensure compliance and mitigate risk, and what specific benefits can be expected from implementing such a project?
5. How will it give our organization a competitive advantage over our competitors, and what benefits can be expected as a result of these improvements?

Addressing these questions requires a thorough understanding of the role of data management in enhancing various aspects of business operations.

Driving Revenue Increases Through Data Management

Effective data management can enable increased revenue by improving the quality of business intelligence and decision-making processes. For instance, high-quality data can enhance data-driven decision-making, thus increasing profitability. Simultaneously, it can reduce costs by eliminating the need for manual data cleaning.

The potential of data management extends beyond direct revenue increases. It also provides opportunities for improved operational efficiency, better customer experience, and compliance and risk mitigation, all of which contribute to a more competitive business.

Exploring Obligations and Opportunities

A comprehensive understanding of data management’s value must consider both obligations and opportunities. Organizations have an obligation to manage their data appropriately, ensuring compliance, security, privacy, and risk management. But beyond these obligations, there are numerous opportunities to leverage data as an asset – through analytics, digital disruption, and transversal initiatives.

To illustrate the true value of data management, let’s consider two examples…

Example 1: Compliance and Risk Mitigation

Challenge: New ESG (Environmental, Social, and Governance) reporting regulations threaten significant fines for non-compliance.

Data management case: Many master and reference data repositories lack environmental footprint details, making ESG reporting compliance impossible.

Result: Effective data management avoids future fines related to ESG reporting, providing cost avoidance.

Example 2: Better Customer Experience

Challenge: An organization wants to gain market share by leading in customer experience.

Data management case: Advanced analytics, machine learning, and AI are hindered by poor data quality, necessitating an investment in the data foundation.

Result: Improved data quality enables prescriptive analytics to capture the market, providing a concrete roadmap for market share increase.

These examples highlight the range of benefits that can be derived from a thoughtful and strategic approach to data management. It’s not just about fulfilling obligations – it’s about seizing opportunities.

A Real-World Application of Data Management: A Case Study

A concrete example often illustrates the value of strategic data management better than abstract principles. This case study involves a client who employed a dual focus, addressing both immediate business issues and long-term success, by implementing short-term technical algorithms and establishing best practices and technology for future organizational needs.

Situation and Complication

The client’s current BI tool was nearing the end of its service life. The tool was highly valued for its role in generating sales and margin reports, critical to valuing the company quickly with reliable data. However, the organization was decentralized, lacked a central master data management approach, and struggled with an undefined approach to product quantities.

These complications presented a clear risk. Without a quick replacement BI tool, the organization would lose insights into its sales performance, which could cause dissatisfaction if the new tool failed to match the old one’s capabilities. Further, the undefined master data made it impossible for management to value the global entity using quantities and margins. The absence of a governance framework meant a lack of oversight on data quality and unclear roles and responsibilities in data creation and maintenance.

Questions and Answers

The situation raised three essential questions:

1. How can we ensure a seamless transition from the current BI tool and meet the needs covered by the old tool?
2. How can we quickly access trustworthy financial data for management to use master data for valuation?
3. How can we ensure long-term, sustained master data quality?

The answers to these questions lay in a multifaceted approach:

1. To ensure a smooth transition, the client decided to implement a customized Power BI reporting tool that replicates the main functionalities and report designs from the old tool – Their obligation
2. For short-term access to reliable financial data, the team defined master data policies and employed mapping tables and algorithms in the data warehouse data flow – their opportunity
3. To guarantee long-term data quality, the client created a data management and governance framework, which included defined roles, processes, and appropriate technologies – long-term enabler/ complication remover

Business Drivers for Adopting Exmon as the Data Management Platform

The client’s choice to adopt Exmon as their data management platform was driven by several factors:

1. The existing rules in the data warehouse were not scalable
2. The current model was deemed ‘too technical’
3. There was a need to improve user experience and install a data quality mindset
4. Other product and customer master data were at risk
5. There was a need to align data across various systems, such as ERP and CRM
6. There was a requirement to extend to other domains
7. There was a need to maintain policies and procedures in a user-friendly manner

Through this real-world application, the client was able to address immediate business challenges while laying the groundwork for long-term success in data management. This case demonstrates the importance and benefits of strategic data management in practical business settings

The Ultimate Goal of Data Management Initiatives

The primary aim of any data management initiative is not just about managing data better or improving its quality. At its core, it’s about addressing specific business cases, solving pertinent issues, and unlocking opportunities for organizations. In a nutshell, it’s about aligning data management solutions with a company’s strategic objectives and using data as a lever to drive business results.

The phrase by Fredrik Ekman, ‘The true value of effective data management lies not in merely improving data quality, but in addressing the business challenges faced by organizational leaders,’ aptly encapsulates this idea. Data management is more than just a technical task; it’s an essential strategic function that enables an organization to leverage its data assets effectively to drive business outcomes.

Data management, in its most effective form, serves as a conduit to a larger goal: it enables the resolution of business challenges, optimizes operations, enhances decision-making processes, and uncovers opportunities for growth. The more adept we are at identifying and resolving genuine problems with data, the greater our potential for enhanced data quality and leveraged use of data.

Thus, the ultimate goal of data management initiatives is twofold:

1. To optimize the way data is collected, stored, organized, and used, thus ensuring it is reliable, accurate, and accessible for those who need it, and
2. To employ this high-quality data to solve real-world business challenges and drive business performance.

Clear communication, strategic problem-solving, and a keen understanding of business needs are therefore key to unlocking the full potential of data management. Data management is not an end in itself, but a means to the end of better business outcomes. It is a vital strategic tool that, when wielded effectively, can significantly enhance a company’s operational efficiency, competitive advantage, and overall success.

Data Management – The Lever to Business Success

As we’ve journeyed through the world of data management, it’s clear that it plays a pivotal role in the success of any modern business. The reliance on high-quality, well-governed data has never been greater, and the impacts of poor data quality are being felt across industries, affecting both operational efficiency and strategic growth

The alarming failure rates of business intelligence projects, with an estimated 70-80% not reaching their objectives, underscore the importance of effective data management. These failures, attributed to poor data quality, misalignment of technology and business objectives, lack of talent, and insufficient executive support, indicate an urgent need to revisit data management strategies.

Data management is more than a purely technical task – it is a strategic function, a means to an end. Its ultimate goal is not merely to improve data quality but to solve specific business problems, enhance operational efficiency, and open new opportunities. It is about understanding and fulfilling business obligations while seizing opportunities to leverage data assets to their fullest potential.

Businesses that treat data as a valuable asset, and not just a byproduct of their operations, can unlock immense potential. Effective data management can increase revenues, enhance efficiency, deliver better customer experiences, ensure compliance, and provide a competitive edge. However, to truly capitalize on these benefits, businesses must approach data management with a clear understanding of both its immediate and long-term value.

The world of business today is data-driven. As the amount of data we generate and handle continues to grow exponentially, so does the importance of managing it effectively. Businesses need to embrace data management not as an obligation but as a strategic enabler of growth and competitiveness.

So, don’t just manage your data, leverage it. Make it work for you. Harness the power of effective data management to drive your business forward. From increasing revenue and improving efficiency to delivering better customer experiences and ensuring compliance, the benefits are manifold. Don’t miss out on the opportunity that effective data management presents. The future of your business could depend on it. 

Talk to an expert today to unearth your data management business case.