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Debunking Eight Common Misconceptions of Digital Transformation

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This is the first of a three-part series about the best practices and most important factors to consider when undergoing a digital transformation.

Separate the hype from reality

Digital transformation?? Oh, not again! Everything seems to be a digital transformation today and there’s nothing left under the sun that hasn’t been written about such disruptive change. One may think. A lot of tales are passed from one digital guru to another that don’t consider the realities of many established enterprises. That’s why we felt the need to demystify digital transformation, separating the truths from the myths based on our hands-on experience.

 

(1) Start with the external customer

Focusing on your customers’ needs and making the digital experience more convenient than the offline experience is at the forefront of many digital transformations. However, most of the cost, speed, and quality improvement opportunities will have internal customers. Each facet of the organization must have a clear understanding of who they support, what their needs are, how they are already using what is provided, and what bandages are being applied. This becomes tangible by simply talking with each other, establish structured interviews, and put yourself in their shoes throughout the process. In turn, the business case must consider both external and internal customers to enact real change.

(2) It needs to be radical

Under pressure to come up with a groundbreaking North Star? Design thinking tells us to put smart people in a room, challenge them, make them uncomfortable, and make sure they know what problem they are solving—as long as it’s radically different from today’s processes. Although design thinking can be helpful, it cannot be used to drive every workshop and ideation session. In reality, every digital transformation won’t be radical, but when it is, three aspects are most important: a minimum viable product (MVP) must serve as a stepping stone toward the end goal, multiple rounds of use case focused initiatives are necessary to build competencies and capabilities, and the business case must evolve from MVP to stepping stone to North Star. Think big, but prioritize what drives the financial impact, even if it’s incremental.

(3) Disrupt yourself before others do

Disruption is coming, but keep in mind two seemingly contradictory concepts: Ignoring your incumbent products or revenues while being obsessed about start-ups, venture capital, and labs will kill the company in the short term, but focusing too much on the healthy margins of the legacy business might prevent a viable future. Nobody can afford not to fight on both fronts, yet there isn’t a single case where aggressively disrupting a core business has been value accretive for shareholders—no matter how cool “disrupt yourself” might sound. Don’t disregard the cash cows and don’t pretend you have the secret to upending your own historic practices.

(4) We need to be agile, scrum, SAFe

At their core, digital programs create ways to work across functions. What works for a major tech company may or may not work for your organization. Of course, digital transformations require MVPs, iterative testing, and flexibility, but throwing a few scrum masters into the legacy organization while management keeps asking for stable plans, business cases, and hierarchical decision making is a recipe for failure. The results of A.T. Kearney’s 2015 Leadership Excellence in Analytic Practices (LEAP) study still hold true in the need for “trilingual” talent well-versed in the languages of analytical modeling, technology, and business. Furthermore, digital transformations need to consider the holistic organization design, talent recruitment and management, and meaningful cultural change to achieve their targets – much more than just ways of working.

(5) AI and RPA will solve everything

Technologies are important, but deconstructing a laborious process into individual parts is fundamental to understanding where and how to apply new technology. Artificial intelligence (AI) and robotic process automation (RPA) are having a profound impact on the fundamental components of many businesses—from financial reporting and inventory management to customer service, but both require a deep understanding of the problems and processes they’re attacking to make the difference. Disregard any vendor or self-declared guru who says, “RPA will reduce costs by X percent or more” without being able to walk you through the individual steps.

(6) Build a data lake, and the analytics will flow

It’s a safe bet that consolidating legacy and local systems will add value, but any digital transformation that is not closely connected to the desired business outcome will never end and is likely to favor the past instead of the future. Visioning the end objectives and solutions that future analytics will enable can be invaluable to back-cast what type of data structure, data types, and data acquisition strategy will be needed, otherwise the organization will fall into a trap of hoarding data without a purpose. Long-term success requires creating a proper data management structure based on the end objectives. Think about this in terms of data definition and quality, governance, storage, integration, presentation, and access and archiving.

(7) Become a start-up

Forward-thinking companies instill speed and accountability in everything they do. They use MVPs, and they remove silos, but they also recognize where being more like a start-up makes sense and where it doesn’t. For many start-ups, focus is at the core of their success. Many large multinational enterprises, however, have an array of commitments that prevent a start-up culture from simply being flipped on. Instead, assess from the top down when to make and when to buy. In our next article in this series, “Corporates and Start-ups – Clash or Synergy,” we discuss how to engage start-ups and integrate their capabilities to get the best of both worlds.

(8) Where we’re going, we don’t need humans

Automation does reduce headcount, but it also requires high-cost data scientists and engineers to maintain it and serve as a co-worker of sorts on the more creative tasks —at least for now. The investment is worthwhile, but it must be accounted for in cost and timing. Finding and hiring these experts won’t be easy as you’ll be competing with big tech and other companies that understand the power of analytics. Plan the investment, and start recruiting immediately.

Of course, these preconceived ideas are not purely myth or truth. Understanding reality, cutting through the hype, and involving the right cross-functional experts are essential steps in any digital transformation. Done right, the impact can be massive. Gather the right team, challenge yourself with new ways of thinking, and you’ll see significant changes across cost, quality, and speed.

In our next article in this series, we discuss “Corporates and Start-ups – Clash or Synergy”

Original Linkedin article


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