Click to learn more about author Kevin Campbell.
As enterprises continue to transform their legacy technology into tools fit for the modern age, digital transformation has become the key buzzword describing this transition into the 21st century. According to Gartner, digital transformation is a top priority for at least 91% of organizations, and yet despite this huge buy-in, only 40% of organizations are realizing their digital transformation goals, according to this same report. One main reason their efforts fail? Leaders don’t consistently prioritize data as the backbone of their success when they look towards solutions around scalability, AI/ML, cloud models, and digital dexterity, to name a few.
Despite the appeal of having the hottest, most up-to-date features in your application and technology stack, neglecting to bring your data into the 21st century is like connecting a brand-new computer to an original monochromatic computer monitor. To oversimplify the analogy, the output and display might work if you’re lucky, but the likelihood for failure is high and performance will suffer.
When it comes to data, enterprises can agree on one thing: Data is a critical success factor and it sits at the heart of company’s ability to make decisions with confidence. And the benefit of having trustworthy and understood data is undeniable. Poorly managed or bad data costs businesses an average of $14.7 million every year, according to Gartner. On the flip side, according to a McKinsey & Co. report, by implementing Data Management at scale, a company with an average IT budget of $1 billion can generate savings of between $70-100 million annually.
In order for your digital transformation to succeed, it is important to start with the goal of creating trusted and understood data throughout your enterprise. A recent HFS Research survey found that only 5% of Global 2000 enterprise executives fully trust their data, yet 90% of those same executives cite data as a critical success factor, since it’s trustworthy data that allows digital systems and analytics to function at optimal levels.
As you begin to prioritize your organization’s digital transformation, consider the following steps to create a Data Management strategy that delivers trusted and understood data:
Look at Data as an Asset on Your P&L Statement
In order for data transformation to succeed, executive sponsorship is a must. Many C-suite executives continue to view Data Management as a back-office function, with management responsibilities falling solely on IT departments. As a result, business leaders rely on IT to solve data issues that are often avoidable at the source, and solving these issues begins with ensuring a proper Data Management strategy is in place. According to the aforementioned HFS Research survey, however, only 23% of enterprises execute a consistent, policy-aligned Data Strategy at scale.
Data strategies begin with understanding the difference between tactical and strategic views of enterprise data. Tactical views on data create reactive Data Management efforts that generally fail to solve the foundational causes of bad data operations. However, when you identify and prioritize the business-critical data for your operations, you can begin implementing processes and procedures that yield positive business outcomes and rapid return-on-investment. This approach sets you on the path toward an effective, strategic Data Management program.
Achieve Business Objectives Through Effective Master Data Management Initiatives
When implementing a Master Data Management (MDM) project, analysis-paralysis can set in for many companies. Where should you start with MDM? What should your first project be?
First, you need to identify the goals and business outcomes you’d like to achieve with your MDM project. Next, determine the ROIs and KPIs to measure for success. Leaders know the biggest pain points that cause business disruptions and these pain points are often the best places to start your MDM project, particularly when they are tool-driven. The most important part in driving a successful MDM project is staying true to your initial objectives. Quick wins that prove value are the foundation to getting larger buy-in to scale these projects in terms of complexity and to other business units.
Finally, find a knowledgeable partner to guide you through the successive phases of MDM projects. Beyond the technical aspects of being able to help you assess, evaluate, design, build, test, and deploy your project at scale, your MDM partner needs to assess your organization’s Data Management expertise, and incorporate testing throughout the design and build phases, especially when your end-users can’t heavily participate in these phases. They’ll also help you through the deployment window where you fold in your training, change management, and iteration phases.
Celebrate Data-Consciousness in Your Culture
If you’re an old-school proponent of relying on that gut feeling to make business decisions, you’re setting your business up to struggle. Every business event now has a digital footprint providing datasets to inform your decision-making. However, data-driven decision-making is only as good as leaders’ confidence in their data.
To get to this point, good data begins at all organizational levels, and that starts with creating a data-conscious culture. Data-conscious cultures embrace the intrinsic value in data but also appreciate the fact that trustworthy data leads to timely and effective decision-making and puts data at the center of important decisions company-wide. Data’s increasing importance is evidenced by the focus on integrity and security across a company’s eco-systems and through governance and compliance initiatives.
Digital transformations succeed only when leaders prioritize data on their journey. Your data partner should be equipped to support your organization throughout your entire data journey – from data strategy efforts, to data migration and M&A assimilations, to MDM projects regardless of your data maturity, all while helping you embrace the benefits of a data-conscious culture. Through trust and assurance of data, organizations position themselves to have better business outcomes, stronger strategic planning, and positive returns.