Three Crucial Phases of a Digital Transformation Journey

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Click to learn more about author Kristian Kalsing.

In today’s digital era, organizations require a solid foundation of trusted master data to enable impactful digital transformation (DX) efforts and drive better business results at scale. All businesses, regardless of industry, recognize that to succeed and deliver the best-in-class customer experience needed for retention and expansion, they must adopt digital transformation initiatives. What some organizations may not realize, however, is that these initiatives are based on and built off of trusted master data

Businesses are more intertwined than ever before, with a plethora of dependent links within a modern product chain. For example, you can have a dishwasher delivered to your doorstep by one company (Home Depot), that was made by a different manufacturing organization (Whirlpool), that’s shipping from a factory somewhere else entirely. So, one kink on the part of either the retailer, manufacturer, or distributor can disrupt the whole chain. With this, operating across systems and data silos is no longer an option, as a supply chain relies on these manufacturers, suppliers, and distributors in disparate locations and often across varying environments to be successful end-to-end. As such, businesses today require integrated enterprises built on data relationships and a connected ecosystem based on a trust network to maximize long-term return on DX spend, pursue new business models, and gain operational efficiencies.

To better understand how to get trusted master data across your enterprise to support and transform data silos into a connected ecosystem, we must first take a step back to understand the critical phases that all organizations tend to move through as they embark on a digital transformation journey:

Legacy State

Naturally, as businesses scale and evolve, they grow in complexity. This initial phase often results in fragmentation, operational barriers, and difficulties scaling. Several aspects of the operation yield further discordance. For example, persona-based tech stacks may offer additional flexibility, but often create more data silos and the potential for further duplication. Separate departments, regions, channels, and go-to-market initiatives across multiple systems and workflows result in siloed data and disparate data sources that lack internal standards. Additionally, relationships such as customer, vendor, partner, and prospect – as well as other important commercial entities, brand, product, and service – often have different definitions across various parts of the same organization.

While most enterprises have adopted modern technology and infrastructure, many remain in some aspect of this legacy state. As businesses look to complete phase one and move towards phase two, they must take the holistic steps necessary to put relationships at the center of their processes to establish trusted master data and seamlessly connect at the data layer. 

Establishing Relationship Centricity

Relationship centricity puts business relationships at the center of any enterprise activity, strategic or systematic, to achieve a consolidated view of relationships and brands across the entire enterprise. This is a critical component of phase two, as relationships are the key to business success, irrespective of industry. Despite many organizations claiming to be “customer-centric,” many often do not have data to support that assertion. To achieve true DX success, organizations must embrace a relationship-centric approach by creating innovative experiences for relationships and brands across the entire enterprise.  

To achieve an integrated enterprise, organizations must establish and govern a common version of the truth about relationships. It is also crucial in today’s highly regulated digital business era to know your customer (KYC) in order to help them remain in compliance and accordance with compliance trends and data privacy regulations, such as GDPR and CCPA, which require a consistent shared view and definition of each unique relationship within an enterprise ecosystem. Only after this is mastered can organizations enter phase three.

The Connected Ecosystem

Phase three comes after organizations achieve relationship centricity. Once that’s accomplished, they can establish initiatives including multi-channel e-commerce, customer self-service, and supplier onboarding by engaging with trust networks across connected ecosystems. “Trust networks” help to engage, interoperate, and seamlessly communicate with different partners across various value chains – including channel partner platforms, e-commerce customer self-service, supplier on-boarding systems, vertical industry identifiers/standards, and programmatic marketing – to deliver a foundation of trusted master data across the entire ecosystem.

Ecosystems are meaningful only when built on accuracy and trust. In many cases, strong business relationships can sour quickly if the data supporting that relationship is inaccurate, outdated, and unstructured. Leveraging common data and syndicated processes allows interoperability in a trust network to scale. To deliver seamless integration and ensure customer satisfaction, businesses should enforce using the same standard data and definitions, or links to the same standard data and definitions, across verticals and markets. This is essential to successfully completing phase three.

How you manage, master, and structure your data will determine your fate within your digital transformation journey. Organizations must move from a legacy state of multiple data silos toward an integrated enterprise built on data relationships and onwards to achieve digital transformation success through a connected ecosystem based on a trust network. Those who succeed at transitioning to the third phase will not only be the leaders of the future but will spawn disruptive innovation, new levels of customer experience, and unprecedented business value. It’s only here that organizations can maximize long-term return on their DX spend, pursue new business models, and gain operational efficiencies.  

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