Enabling Business Execution through Great Architecture and Application of Technology
An organization’s technology leader in 2017 faces a dizzying array of rapidly evolving technologies, which are creating interesting opportunities, and of course, amounts of data beyond all prior imagination. For most of our careers, technology has always helped enable better business outcomes. The velocity of technology change today seems to increase every month. For those who have the right vision and follow the right path, there is a distinct opportunity to create significant rewards for your organizations.
The interesting challenge most of us face today is in fully understanding these rapidly evolving technologies while thinking through business implications. At the same time, creating a thoughtful modernization strategy for your legacy assets needs to balance investments in new technologies and capabilities with legacy retirement activities.
Traditionally, business leaders were able to learn from competitors and make fairly informed technology and/or project requests of their technology counterparts. Today, technologists are struggling to fully understand the implications, benefits and business value of new capabilities that are being introduced, let alone their partners in their business community.
The challenge of the next decade will be how to access and to evaluate data outside of your company
So why is this different than any other time in the last 30 years? Historically, the technology leader’s role was clear—deliver what the business requested and make sure projects were delivered; albeit usually late and over budget. This was fine when technological advancement was measured in client-side MHz and in-memory RAM improvements and major projects in years. Velocity of change is now being driven by a number of underlying enabling technologies—relatively cheap compute and storage, massive parallel processing, machine learning, smartphones, and connected sensors. The impact of these technologies is exponentially changing our marketplace.
For example, smartphones were not a ‘thing’ 10 years ago. Today, 77 percent of Americans own a Smartphone, up from 35 percent in 2011, and over 10 percent of American adults use a Smartphone as their only source of connectivity. Six months after a startup, I founded in 2013 launched, 30 percent of our site traffic was on mobile devices. Six months after that, 60 percent was mobile.
Similarly, an organization had to manage gigabytes or terabytes of data—and now customers and third party data sources are with machine learning have created an ability to comb through petabytes of data with self-learning algorithms dynamically testing and finding new correlations and even developing inferences.
These tools, the relative low cost of entry, billions of dollars in corporate, and venture capital investment are yielding new insights and better ways to meet consumers’ unmet needs every day. Want to measure where a car is and how it is being operated based on the driver’s phone? No problem. Want to evaluate crop moisture levels and optimize irrigation practices? Done. Want to have product line create its own optimized product assembly flow based on real time consumer demand? Sure.
The fundamental difference now is—we can. The questions that researchers and business people have worked on for decades are now being answered in days not years: What is the genome sequence of a particular cancer, how do I better understand my customer’s preferences? Since companies started collecting data in the 1950’s, until now, an organization’s analytics exercises were attempts at understanding the world through the lens of their internal data. The challenge of the next decade will be how to access and to evaluate data outside of your company, then in concert with your internal data, develop answers to your business’s most pressing unanswered questions.
Given this cocktail of tools and capabilities, it is hard to imagine how different the world will be in 10 years. To the extent one places value in anecdotal conversations, there is unanimity among the leaders with whom I discuss these things that dramatic changes are coming. So, the question is, how best to prepare?
Start with your vision and your technology leadership team. Are you going to migrate your organization to a public cloud? Are you going to invest in people and assets to better understand applications or machine learning? If you are unsure, what interim steps do you want to take to help better understand risk, benefits, and develop information to help make your case for change? If your agenda is focused on driving change, what is the next step to get your team behind the case for change? If you don’t have a great enterprise architect, this is where I would start. Complexities of how different technologies work together and how to manage data and data flows around your organization are very important to understanding where to invest.
Create an Architecture that is Modular - enough to replace components without major project spend. Utilizing open-source tools to create cost and capability advantages, and is flexible enough to adapt as new products, tools, and capabilities.
Go all-in with Digital - The days of dipping one’s toe into the ‘digital’ pond are coming to an end as consumers choose to interact only with companies who deliver the integrated set of functions/capabilities they demand. The biggest challenge, depending on your current state, will be making the case for change to your business leadership and potential board. Getting the capital and the time to evolve is critical to success.
Finally, your team and the technology capabilities it delivers has to support serving up data the customer needs, on the device a customer wants, whenever they want it. The choices you make today with investments in your capabilities may create optionality with your IT assets, capabilities you may bring to your business partners, and all potentially at a more efficient operating environment (more capability and lower cost). Success will be a balancing act between the business needs of today, the evolution of your enterprise architecture, and understanding the changing expectations of your end users.
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