In this special guest feature, Kevin Campbell, CEO of Syniti, argues that digital transformation is data transformation, and for enterprises to have a successful digital transformation, their data transformation must be a priority. As CEO, Kevin drives the growth agenda of Syniti with poise and at ease. With a solid track record in driving growth at scale, Kevin joined Syniti as president, global consulting and services April 2018, and was named as CEO in February 2019. His leadership remit here is simple: Inspire and empower those around him to deliver on the business’ vision and purpose. He oversees all aspects of our operation while also taking every opportunity to engage with customers, partners, and employees on the ground around the world.
Ninety-one percent of enterprises are embarking on transforming their legacy technologies into 21st-century digital tools, according to a 2020 Gartner report. One major part of this journey is data. Despite this large-scale initiative, enticed by aspirations to improve business processes and increase revenue, only 40 percent of organizations are succeeding in their digital transformation efforts, according to this same report. With a precision focus on deploying digitalization, IT leaders are looking for solutions that checkmark all of today’s industry demands scalability, AI, machine learning, cloud models, and digital dexterity, to name a few.
While all these features bring incredible value-add to business transformation, leaders are neglecting one essential asset, if not the most important, that accompanies a successful digital transformation: data. This underlying commonality provides enterprises petabytes of structured and unstructured datasets that can inform business decisions. And managed poorly, bad data costs businesses an average of $10.8 million every year. However, the cost of implementing data management at scale is projected to achieve 10 percent or more revenue growth – three times the average – while increasing risk mitigation and providing better customer experiences, according to the same Gartner report.
Digital transformations must begin with data transformation and getting there starts with trusting your data. According to a recent HFS survey, only five percent of Global 2000 enterprise executives trust their data, yet the pillars of digital transformation rely on data at their cores to function.
As companies continue prioritizing their digital transformation, here are some key considerations for a strong data management strategy that will create a robust data infrastructure:
Treat Data as a Strategic Corporate Asset
Without executive sponsorship, data transformation is bound to fail. Too often is data management viewed as a back-office function that IT departments are responsible for managing. However, when data isn’t right, business leaders turn to IT to fix these often-avoidable data mistakes when a proper data management strategy is in place. Businesses need to start taking ownership of their data, which begins with driving processes to strategize data. This process begins with understanding the difference between a tactical and strategic view of enterprise data. Many companies are reactive to data management, which aligns with a tactical view that never solves the root cause of bad data operations. When you understand what data are critical to the business operation and how to implement processes and procedures that yield positive business outcomes, enterprises finally shift toward a strategic approach.
Align Master Data Management Projects to Business Objectives
Many companies find themselves in gridlock when implementing a master data management (MDM) project and are plagued by the where and the how to start. For simplicity, start by backward planning – that is, identify where you want to end up first and then determine the ROIs and KPIs you want to measure to tell a success story. The easiest place to initiate an MDM project is to identify your business’s most significant interruption points, especially if these are tool-driven versus people-driven. Be sure to stay true to your initial objectives because by driving quick wins that prove value, you can grow a larger buy-in pool to advance other projects.
Next, find a partner who can walk you through the successive phases of MDM projects. This partner should be able to help you assess, evaluate, design, build, test, and deploy your project. Beyond the technical aspects, this includes assessing your organization’s data management expertise, testing throughout the design and build phases, especially when your end-users can’t heavily participate in these phases, and ultimately through the deployment window where you fold in your training, change management and finally iteration phase.
Embrace a Data-Conscious Culture
The days of solely relying on gut instinct to make business decisions are over. Every business event now has a digital footprint that should drive informed decision-making. However, good data begins at all levels of an organization. By creating a data-conscious culture, organizations are embracing not only the intrinsic value in data but also understanding the value between its availability to the timeliness of decision-making, the importance of its integrity and security across an organization’s eco-systems, and its importance through governance and compliance. As opposed to data-driven, data consciousness emphasizes that relying on data alone can be just as dangerous as ignoring it altogether.
For digital transformations to succeed, data transformations are vital. Make sure your partner is equipped to guide your organization through MDM projects regardless of the organization’s maturity and embrace the benefits of conscious data culture. Through trust and assurance of data, organizations will set themselves up for more efficient business outcomes, strategic planning, and positive returns.
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