The greatest challenges facing humanity in the 21st century require that we do a better job of integrating people, processes, and technology. Whether we’re talking about how to distribute medicine and doctors to solve a health epidemic, or looking to reduce supply chain risk in a complex multinational organization, we must use computers, data, and our own judgment in unprecedented ways.
The good news is that there’s a simple way to think about how we can work together with data and other experts in complex situations. The map is shown in the figure below; you’ll find that this is the “skeleton” for all complex decisions. Although Decision Intelligence uses the most sophisticated technology, its core principal is to minimize the “friction” between people and these systems so that we can work in partnership. The simplicity of Facebook combined with the power of IBM’s AI computer, Watson, accessible to all: that’s the vision for Decision Intelligence.
Imagine the head of an NGO in Africa, faced with combating a new disease, with limited donor funds, and with the goal of avoiding “band-aid” solutions, instead providing a new system that lasts well beyond the current crisis and well into the future. He needs data about the disease, for sure. But he also needs to understand where money is best spent: should it go to hospitals? Doctor training? Community health workers?
Where are points of leverage in this system, where a little goes a long way, and a “tipping point” changes a cycle of disease into a cycle of rebirth? And where are the holes into which money can flow, producing little-to-no benefit? To answer this question, our NGO friend needs to understand how his decisions interact with the situation on the ground. And then, as the fluid situation changes, he needs to navigate to a new decision a few weeks later.
Or imagine the head of a project inside a large bank, tasked with transforming thousands of buildings to use a new communications technology. He’s got a giant database of information about each building, and the electricians, construction workers, and telecom contract terms. But it doesn’t tell him how to schedule his work to maximize the business benefit.
Like so many decision makers in complex situations, he’s got great information on the situation, but less help with his decisions in that situation, and how they can lead to multiple objectives: financial (short- and long-term), environmental, and societal.
If this sounds like you, someone you know, or someone you’d like to help, or if you’re just fascinated by the technology and how it all fits together, then I invite you to join me on this journey through reading this blog, and more importantly, sharing your thoughts and comments. I’m passionate about decision intelligence, and will share with you my thoughts and analysis of news in the DI world, in all its facets, including data science and specific vertical application areas like sustainability and government budgeting. I’m glad you’ve read this far, and I hope you find this blog useful.