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The title might sound like a movie but this article is about unpacking decision making. We need leaders to be confident in their decisions so we can hold them accountable. We desire leaders to lead, wanting them to be early. They achieve this by listening to the signals and reacting before is is obvious to the casual observer. However, those in leadership who we hold accountable do not want to make the “wrong” decisions. A wrong decision can mean liability, loss of reputation or perceived to be too risky. A long senior leadership career requires navigating a careful path between not takingtoo much risk by going too “early”, which leads to failure, and not being late such that anyone could have made the decision earlier and looking incompetent. Easy leadership does not look like leadership as it finds a path of not being early or late (the majority) When we unpack leadership trends over the past 100 years that include ideas such as improving margin, diversification, reduction, spee

In the week where the worlds “leaders” meet to discuss and agree on the future of our climate at  #COP26 , I remain sceptical about agreements.  At #COP22 there was an agreement to halve deforestation by 2020 ; we missed it, so we have moved the target out.   Here is a review of all the past COP meetings and outcomes. It is hard to find any resources to compare previous agreements with achievements.  Below is from the UN.  The reason I remain doubtful and sceptical is that the decision of 1.5 degrees is framed.  We are optimising for a goal.  In this case, we do not want to increase our global temperature beyond 1.5 degrees.  Have you ever tried to heat water and stop the heating process such that a temperature target was reached. Critically you only have one go.    Try it. Fill a pan with ice and set a target, say 38.4 degrees, use a thermometer and switch off the pan when you think the final temperature will be your target. Did you manage to get within 1.5 degrees of your target? 

Are the consequence of a ½ baked decision that we created ( the mess we are in ) squared This article joins how the # climate outcomes we get may be related to the evidence requirements we set.  The audience for this viewpoint is those who are thinking about the long term consequences of our current decisions and the evidence we use to support those decisions. We are hoping to bring a sense of clarity to our community on why we feel frustrated and lost. You should read this because it will make you think and it will raise questions we need to debate over coffee as we search to become better versions of ourselves.  @yaelrozencwajg @yangbo @tonyfish The running order is: Which camp are you in for positioning of the crisis: know and accepted, still questioning or denial.   What are the early approaches to solutions?  What are policymakers doing and what is their perspective.  The action is to accept the invitation to debate at the end. Part 1. Sustainability set up The world appears more

What are we asking the questions for? This link gives you access to all the articles and archives for </Hello CDO> This article unpacks questions and framing as I tend to focus on the conflicts, tensions, and compromises that face any CDO in the first 100 days — ranging from the effects of a poor job description to how a company’s culture means that data-led decisions are not decisions. I love this TED talk from Dana Kanze at LSE.  Dana’s talk builds on the research of Tory Higgins who is credited with creating the social theory “ Regulatory Focus ”  This is a good summary if you have not run into it before. Essentially the idea behind “Regulatory Focus” is to explore motivations and routes to getting the outcome you want. The context in this article is to explore how a framed approach to questions creates biased outcomes. One framing in Regulatory Focus centres on a “Promotion Focus” which looks for “ gain ” which can be translated as finding or seeking hope, advancement a

Many ask the question “can AI be ethical?” which then becomes a statement “ AI must be ethical! ” In reality we do not tend to unpack this because it appears so logical, but maybe it is not as obvious as we would like. In May 2021 I wrote this article “ What occurs when physical beings transition to information beings? ”  It started to question what happens when an AI does not have the same incentives and bias as humans.  It was building on this the idea that an # AI should not make complex decisions about wicked problems that involve compromise.   There is an implicit assumption in the question “Can AI be ethical?,” that AI is either fundermentall not ethical or is already amoral today but #AI must somehow become ethical and have morals. (or worst it must adopt ours.)   I am not sure AI cares if it is ethical or not but that is a different piece of thinking which I explored here “ Can AI be curious? ”.  We know carbon forms can be curious but we worry about a silicon form being curi

Click here to access all the articles and archive for </Hello CDO> Day zero, you have arrived and you have 100 days to plan. ( H 0 ) How do you determine if your new company is addressing the underlying issues that hold back data from being what they imagine it can be?  The issues that hold back an organisation from really capturing the value of data are at a  minimum: org structures, people issues, a lack of accountability, and incentives. Whilst having a CDO, doing data science, having analytics, using artificial intelligence, testing data quality, and a world class data governance structure make a difference; true transformation will remain a struggle if the structural issues remain. The question is how do we, as a CDO, test the fitness of our organisation's preparedness for data.  If the results are acceptable to the leadership team is one of politics and is way beyond  the scope of this article.   To test the fitness of your organisation's preparedness for data, it