What To Look For In A Data Leadership Role A few months back, we shared a series of articles to help analysts and data scientists choose their next role (parts 1, 2, 3 and 4). Here, I expand on
Beware Tech Advocates Bearing Certainty Many organisations are forced to take a leap of faith. Under pressure from consumers or shareholders they know they need to transform, but they might not have the comprehension, capability,
How Did Enterprise Data Science & AI Fare in 2019? This is the time of year where many of us find ourselves reflecting on our performance. Did we stick with those New Year's resolutions, or not? Did we achieve what
'Twas the Post Before Christmas (2019 Edition) 'Twas the post before Christmas, fifty-two on this blog, It was due this morning, but Ryan slept like a log; Yet this seems a good time, for the year to
Embed Or Centralise? Where To Build Your Analytical Capabilities When a business reaches the point when it decides it needs dedicated analyst or data science capabilities, one of the first questions that gets asked is ‘where should we put
When Not to Use Analytics In my fifty weekly posts so far this year, almost every single one has advocated for the application of analytics and artificial intelligence (AI). While this is often the most
Data Product Managers, Not Just Project Managers As we reviewed last week, building an impactful data, analytics, and AI capability requires a range of new roles and competencies. While the scope and responsibilites of roles such as
Elements of an Effective Data & Analytics Function What does it take for an organisation to be able to perform analytics in a scalable (read: beyond Excel) manner? When I worked at Google, my instinctive answer would have
Why We Also Need To Talk About Analytics Ethics Over the last few years there has been an increased focus on data ethics. People are waking up to the fact that in many cases it is their data and
CDO? Sadly, Often the CCO is the Real Data Authority I am not a seasoned writer. If I was I would save the punchline for the last paragraph, forcing you to wade through another six hundred odd words. Instead, I
Analysts & Data Scientists, How to Choose Your Next Role (Part 4 of 4) Welcome to the final part of our four-part series on choosing your next data science or analytics role. We have covered a lot of ground so far: from choosing the
Analysts & Data Scientists, How to Choose Your Next Role (Part 3 of 4) Welcome to the penultimate installment of our four-part series on choosing your next analytics or data science role. So far we examined Location & Timing in Part One, and Industry
Analysts & Data Scientists, How to Choose Your Next Role (Part 2 of 4) Welcome to Part Two in our four-part series on choosing your next data science or analytics role. In Part One, we looked at the question of role Location & Timing.
Analysts & Data Scientists, How to Choose Your Next Role (Part 1 of 4) While jobs in analytics and AI can be both exciting and lucrative, employee attrition in these roles tends to be high. It is not uncommon to see data scientists move
The Universal Language of Analytics Arriving in a new country, you are faced with a lot of differences in customs, traditions, and culture. These changes are heightened when you move to a new region entirely.
Why I Am Starting My Job by Stopping This week I started a new job. As this is a role at a different company and in a different country, this means a lot of change. Many people have
The Importance of Knowing When You Are Ready to Make a Decision I am certain that I have on more than one occasion mentioned how important it is to consciously make decisions. Because analytics is the art of making better decisions using
How to Convince Your Management to Take Analytics & AI Seriously As demonstrated by the global demand for talent, most organisations have now woken up to the importance and potential impact of data, analytics, and AI. Yet discussions with employees across
Back to School: Three Things I Learned From a Machine Learning Nanodegree At work I spend a lot of time thinking about machine learning (ML), both in terms of how to apply it and the practicalities of enabling an organisation to do
Evidence Shows That When Making Decisions, People Hate Experiments We like to think that this blog, while born out of a trivial New Year’s resolution, has managed to become a reasonably serious outlet. That said, we fully appreciate
Ask and You Shall Receive - Dealing With Hard Facts In a quote frequently misattributed to W. Edwards Deming, one of the fathers of process improvement, ‘In God we trust. All others must bring data.’. But what if someone brings
If You Are Serious About AI, You Had Better Get Serious About Data Quality Ah, data quality. Almost as unpopular a cocktail party topic as data governance. Yet like that walking punchline Chandler Bing, data quality is about to enter its defining decade. It
Steering The Culture Ship I was in Tokyo a few years ago on business and grabbed a beer with a former colleague of mine. He had moved to Japan from the UK a few
Do Your Metrics Matter to People? From Budget to Behavioural Metrics Another quarter, another review. Your organisation is worried advertising costs are rising. Spend is up significantly on video ads and worse, so is their cost per view (CPV). What is
The Trap of Complex & Easy Instead of Simple & Difficult Have you ever tried to build a strategy around a difficult topic and found yourself overwhelmed by the decisions in front of you? Perhaps it seemed like there was no
