How Business Transformation is Fundamentally Different from Innovation

An interesting debate transpired during the last #CIOChat on Thursday at 2pm around Myles Suer's question, "How is #innovation fundamentally different from business transformation?" I had significant feedback to my tweets and decided to dedicate this week's blog post to detail my perspective.

I provided a two-tweet answer
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10 Questions before starting a Machine Learning POC

37% of organizations have implemented artificial intelligence in some form according to Gartner. Since AI is a a broad category of algorithms covering cognitive, natural language, pattern recognition and other areas, I suspect the number of organizations experimenting with machine learning or deep learning is a lot smaller.

Yet there are daily stories of different organizations benefiting from machine learning algorithms. This week I read about Frito Lay using ML to determine chip texture, MIT reporting on ML used to create extra-delicious basil, and an ML that helps to detect gunfire.

Last week I posted a more futuristic prediction  when software architecture will be driven by machine learning. This week I want to follow up with these more practical steps on getting started with machine learning.
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Beyond microservices; Software architecture driven by machine learning

It's not a question of if, it's a question of when and how AI and machine learning will change our programming and software development paradigms.

Today's coding models are based on data storage, business logic, services, UX, and presentation. A full stack developer elects to build a three-tiered web architecture using an MVC framework. An IoT application calls for an event-driven architecture with services processing events and broadcasting state changes. 

These two architecture paradigms converge with microservice architectures where user interfaces are just one type of interaction node fulfilling high level functions by interfacing with many services.
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5 Ways to Kickoff Data Governance in Self-Service BI Programs

Sponsoring self-service BI where business users are empowered to develop their own dashboards and instrumenting data governance are not conflicting objectives. In fact, they are complementary and both are necessary to enable data driven organizations.

Don't believe me? Go count the number of Excel spreadsheets or GSheets are on your network. Try to count how many duplicate data sources are in these spreadsheets. Open a sample and see if you can find errors from misapplied formulas. I share several of these data sins of the past in my book, Driving Digital.
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The Role of the CIO in Digital Transformation - Live blogging #CIOChat

My notes from Stephanie Woerner of MIT CISR at today's #CIOChatLive forum at Boston College talking about what is digital transformation, paths to get there, and the role of the CIO. It was a great talk with many examples and worth reviewing the actual research.
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Scaling agile? Five important considerations to get it right

Agile is not a cookie cutter framework or set of practices.

I’ve been a part of large number of agile organizations some as CTO, some as CIO, and now as President of StarCIO. Although I’ve reapplied similar agile practices across multiple organizations and teams, none were implemented the exact same way.

Agile can’t be baked into a one size fits most framework. It’s one reason StarCIO brands them as Driving Digital Practices - because they are building blocks that are selected, roadmapped, and adopted to an organization’s culture, goals, and legacies.
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