AI, data, and the future of decision making
What does it mean for an organisation to be future-ready? One part of being future-ready is to be ‘hyper-decisive’.
At the Prophix Conference in Nashville, I heard from a variety of thinkers and leaders who confirmed many of the key traits that I believe offer a measure of future-readiness. And I heard, and presented, evidence of how far from demonstrating those traits, most organisations remain. Our organisations continue to lack agility because we are poor at collecting information, poor at processing it, and poor at taking business decisions on the basis of that information, relying overly on gutfeel human judgement over good, hard evidence.
The future of decision making
A variety of solutions to this challenge were presented at the conference. Polly LaBarre, founding member of the Fast Company team and author of the best-selling Mavericks at Work, talked about a changing culture of leadership, and the shift from enforcing direction to asking questions. Her instruction was to “walk in stupid” each day.
Gary Simon, managing editor of FSN and founder of the Modern Finance Forum, a global network of more than 50,000 finance professionals, highlighted issues from his research into innovation and planning: Most companies still struggle to forecast accurately, reforecast with sufficient frequency, and worst of all, to offer the leadership real insight from those forecasts to drive better decisions.
Howard Dresner, former Gartner analyst, founder of Dresner Advisory Services, and the man who coined the term ‘Business Intelligence’, talked about the concept of companies becoming “hyper-decisive”, leveraging “information democracy” across the organisation to allow strategic decisions to be taken rapidly, by people at all levels, based on solid data.
The age of analytics
Notably, while this was a conference hosted by a technology company, the common theme running through these talks was about skills. Walking in stupid each day is about mastering your own ego, but also understanding what questions to ask. It’s about a fostering a curious, analytical, and most importantly open, mind. Turning numbers into insight is about the technical skills of data manipulation and analysis, but it’s also about skills of storytelling and narrative. Information democracy can only become real if the skills of data literacy are widespread across the business.
Listening to these leaders talk, I was brought back to one of my most common questions, one that I have written about frequently here: What skills do we need for the future? To me, Polly, Howard and Gary all seem to be talking about the three Cs I laid out back in about 2015 (maybe earlier): curation, creation and communication.
All of us need the skills of discovery and qualification, the ability to recognise gaps in our knowledge and understanding, source data to fill those gaps, and validate it (‘curation’). We need the ability to manipulate that information, apply it, and turn it into something of value (‘creation’). And then we have to sell our new creation to our colleagues and customers, wrapping it in a compelling story (‘communication’).
Decisive leadership
Dresner’s vision for the modern management practice continues to evolve, with the idea of being ‘hyper-decisive’ forming the topic of his recent conference at Real Business Intelligence. He defines this as, “instantaneously processing vast arrays of data and information, and delivering actionable insights to a growing community of users.” Technology is clearly part of the answer. It allows us to collect this information in real time, automate some of its processing, and present it in a dynamic fashion. But none of this is of value unless our community of decision makers, across the organisation, is equipped with the skills to use data-driven insights to improve the business every day and foster decisive leadership.
The future of AI in work
The artificial intelligence (AI) goldrush is on. Every company that five years ago was touting its ‘Big Data’ credentials is now referencing AI as a cornerstone of its business. I’ve heard tales of the most unlikely organisations clamouring for AI expertise to help them solve complex business problems.
What we mean by the term AI, is still up for debate of course. Clearly, we don’t mean a generalised intelligence in any way comparable to human. For the most part, we mean some form of machine learning — primarily through large data sets, but increasingly through modelling and adversarial systems — and automated analysis.
Golden data
Data has had a lot of focus as a critical asset, often presented as the gold in this rush. But there are many other critical tools, and the makers of these stand to benefit perhaps more than those holding the data or applying the tools.
The obvious companies here are the tech giants that have developed or offer the raw processing power or the core tools of machine learning: Amazon, Google, IBM, for example. But there are others too — like Bellrock, a company I came across recently that offers a platform for more rapidly applying models to data for predictive analytics.
There are also the companies to whom you can outsource the ‘mining’ of gold — or perhaps a more accurate analogy might be the production of automated mining systems. Consultancies who can build AI tools for organisations to use. From the very large, like Accenture, who recently showed me an interesting demo of automated document analysis for the pharmaceutical sector, to the relatively small, like US.Ai, whose co-founder I met at a BIMA event recently.
Early days
For all the hype, we are in the early days of artificial intelligence. It’s still hard to know what the most valuable applications will be. But while everyone’s trying to find those answers, those companies that provide the shovels for this gold rush are likely to profit. The future of decision making may lie in harnessing the power of data across entire organisations.
