IT Architecture Strategy Sets the Table for “What’s Next?”
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IT architecture strategy is critical to the future of one’s business, regardless of the size of company. Even if a company outsources its IT role to partners and external resources.
An interesting set of IT architecture decisions are about to be made by businesses. The three key decisions impacting the future of business involve choices of platforms: 1) data platform, 2) cognitive/AI platform; and 3) cloud platform.
When these decisions are made, they impact not only selling environments but also lots of downstream environments, as well.
Why? Because according to IBM Chairwoman, President and CEO Ginni Rometty: “We are in a show me, not tell me, world.
If businesses want to compete in the digital, IoT ecosystem, they can no longer put off key decisions with respect to IT architecture strategy.
Up until recently, surveys of business, IT, engineering and operations leaders forecast how companies are “planning” or “thinking about” digitally transforming how they do business. However, very few companies were able to describe business cases where they walked the digital talk from test bed to beta test to full deployment in their company.
As more companies become more digitally savvy and competitive, client expectations are accelerating. “What’s in it for me?” now implies, “How is your IT infrastructure strategy going to translate into delivering business value for my company?
That was the message communicated at last week’s IBM PartnerWorld Leadership Conference in Las Vegas last week.
Regardless of whether you insource, partner or outsource, what does your organization’s IT architecture strategy and stack look like? Where is it headed?
Clearly, the cloud is the preferred platform for business, as it accommodates compliance and security. Advances allow cloud platforms to scale as clients scale their own business models and processes, including sales and service delivery, all requiring insights from data analytics to drive decision making.
In addition, AI (artificial intelligence) is exploding onto the scene. For example, business intelligence (BI) can derive insights from data aggregated by business, including mining social data and driving customer engagement via managing customer relationships. Also, AI can optimize logistics and asset management and tracking.
Then there’s spending on cognitive computing, estimated to reach $31B by 2019. Cognitive computing uses computer modeling to simulate human thought processes and how the human brain works. These models incorporate self-learning systems (machine learning) which mine data and recognize patterns and natural language.
Choices made for IT architecture strategy, function and implementation impact the future of businesses.
Getting clients embedded in your organization’s IT solutions positions you for not just years of growth, but decades of growth. Chew on that sentence for a while.
Enabling clients with data allowing them to make more robust and competitive decisions not only grows their businesses today. These decisions also expand and sustain their initiatives as well as an organization’s tech solutions, services and customer experience strategy partners to meet client strategy.
Having a cloud platform, public, private or hybridized, rapidly is becoming today’s table stakes. However, two key factors emerge as critical to executing digital strategy.
- Data platform. We all agree that there is way too much data being generated, both structured and unstructured. However, data is meaningless without analysis and extraction of insights. How you leverage insights from data creates value for clients. Those insights engage customers, create extraordinary experiences contributing to their success, and consequently drive loyalty and customer retention. What type of data platform does your company leverage to easily extract and leverage insights? How involved is your CIO as the key architect of implementing IT architecture strategy?
- Cognitive platform. It’s not just about speech recognition. When making a decision about AI, a platform must offer a range of services including machine intelligence and competency to learn professional domains. In addition, the platform must offer transparency regarding who taught the system and the source of data used to teach the system. Then there’s the question of an organization’s business model regarding data. Yes, the platform provides the insights. However, those insights must reside with the client instead of a big pool which competitors can access.
The intriguing aspect of investing in a digital IT architecture strategy, today, is that the system acquires greater value over time.
The interplay between cloud, storage, data platform and cognitive system capabilities creates what I call “IoT symbiosis.” This ecosystem is an IT architecture strategy that leverages cognitive platform learning capabilities in product and service delivery from plant floor to C-Suite.
Over time, systems become smarter and smarter. And today’s clients expect systems, software, equipment and customer experience to become better and better over not only the system lifecycle but the customer lifecycle.
As a result, the days of “wishing and hoping and planning” to migrate into a digital business environment are old news. Instead, business cases describe success stories of digital transformation involving people, teaming, collaboration and the interplay of equipment, software and IT architecture strategy.
As Rometty stated at IBM PartnerWorld last week, “The battle of the IT architecture sets the table for the future.”
The relentless pace of digital IoT transformation waits for no one to play catch up. Choices made today impact the viability of your own organization and your clients’ organizations in the future, not just tomorrow.