The Road to Transformation
Having a nice car doesn’t make you a good driver. And, your car won’t help you get to your destination if you don’t know where you want to go. Digital transformation is no different. You need to know what you want to accomplish and plan how you are going to get there. Sure, it sounds obvious. So why do we see so many organizations struggling to make progress? It seems too many organizations believe they can make progress simply by hopping into a taxi and saying, “just drive.” Maybe they need to try Uber.
I am fortunate to be part of the consulting group within Dell EMC. When I took on this role, I was hesitant to work for a product/technology company without a dedicated focus on a specific product set, and instead, devoting my attention on consulting services in the area of Big Data and IoT analytics. This hesitancy stemmed from the fact that, typically, hardware and software are the “hero” products, so isn’t that where I should be making the most impact? Shouldn’t I dig into the technology and learn all about its capabilities and features so that I can help customers along their technology journeys? Well, as it turns out, having a garage full of great cars won’t teach you how to be a great driver, nor will it help you determine the best destination or how to get there. And that’s where consulting services come in.
If you’re reading this blog, you’ve likely seen other insights from my colleagues about the trend of digital transformation– what it is, what it could mean to your organization, and what the technologies are that enable it.
The good news is that the information you have seen is important, and the highly-optimized technologies are available. The bad news is that more than half of the organizations we talk to report that they are struggling to make progress. So what is so hard about this?
I won’t go into another breakdown as to what digital transformation is. But for many, it likely involves the Internet of Things (IoT), big data, analytics, and cloud-native application development (app-dev), and it results in providing timely and predictive insights that help: drive better business decisions, develop new business models, improve operational efficiencies, produce better product performance, drive more effective marketing, enhance customer experiences, and reduce exposure to risk.
That’s a great number of extremely important results. However, driving these changes all at once is too much for any organization to undertake. The list alone indicates that any organization would go out of business if it put all of its attention on doing all of those things simultaneously. And THAT is the first discussion that needs to happen: “What business outcome is the highest priority? What questions do we need to answer to make our most important decisions? And, what data is relevant to being able to answer those questions? (Notice that I didn’t lead with “What technology should we buy?”)
Organizations must ask and answer those questions first by collaborating with IT and applying data science approaches to prioritize the use cases for their data and analytics that will drive the more important business outcomes. As Stephen Covey wrote: “Begin with an end in mind.”
In order to help customers map strategic business initiatives to data and analytics use cases and to determine the ones that have the best combination of business benefit and implementation feasibility, many companies start with a Big Data Vision Workshop. The goal of the workshop is to help the IT and the business stakeholders align to an “end” – a “use case” – the outcome that will be a strategic step toward business transformation.
Organizations that use these approaches can utilize their test environments to pre-confirm the ROI of their use cases. In our consulting engagements, we’ll model a solution (app or process) to show how those insights would be consumed to help make those critical decisions about strategic business initiatives. Part of this ROI process is to determine the technology architecture that is best suited to deliver these results, as well as considering the cost, cleanliness, currency, (and other factors) about the data. After all, the best use case is the one that has the correct combination of business benefits and implementation feasibility. The validated architecture and analytic models are then deployed into production, and we operationalize the analytics and feed the consumable insights to the end-user apps or processes.
For digital transformation, this needs to be a repeatable process – not a one-time science experiment. Guiding customers to adopt app-dev best practices, such as devops, as well as deploy a cloud-native app-dev platform (such as our Native Hybrid Cloud), we observe that customers are speeding time to market while modernizing the application infrastructures for greater efficiencies. This improves the consumability, performance, and adoption of new, high-value, apps, with predictive insights about customers, products, and operations. But there is still more to do. Driving digital transformation requires new operating models, changes in governance, new security measures, new skill sets and processes. These are areas in which services (consulting, education, deployment, support, and managed services) play a big part.
In summary, digital transformation is a necessary and tremendous journey that all organizations must be making. Unless you want to be the next Blockbuster Video, Circuit City, or Borders, you must identify which areas of your organization are the best candidates for digital transformation. Fortunately, this is all very feasible. Begin with your “end in mind,” and you will arrive at a formula to extend transformation across the entire organization.
Jeff Abbott is a Sr. Consultant for Dell EMC Services