helping you master the people side of data & analytics

How to be productive working from home, improving your technology

improving your technology

If your home-based working days are like many leaders, you’re seeing a need for improving your technology daily. You need to make a professional first impression online, more than ever.

Our diaries are filled with more and more video conference meetings. Whether you are using Zoom, MS Teams, Skype or one of the many other apps – you are trying to give your team more face time (excuse the pun).

One day last week I had 9 different Skype meetings in a day! But, as I talk on webcam to other leaders & their teams, I see their need to fix some basics. We know that appearance matters in business, so this post should help you appear more professional by fixing common issues.


How to be productive when working from home, lessons learnt (part 1)

working from home

Although the speed of recent changes for us all has been breathtaking, learning how to be productive when working from home is not new.

Given so many leaders, perhaps including you, are now suddenly facing the challenge of working from home as a new normal – it seems only fair to share. That is, for those of us who have worked this way for years, to share what we have learnt.

Personally, it’s nearly 6 years since I launched this blog & my business, so I hope it helps you for me to share some of what I’ve learnt along the way. I’ve suffixed this blog title with ‘part 1‘ because I hope to have more advice & resources to share. I’ll also be bringing other voices into this conversation. Watch out for new posts & podcast episodes coming soon.


Too big for Agile? Is there a middle ground? (AgilePM 1)


Having recently lectured MSc students on project management, I’ve been pondering the issue of being too big for Agile.

Like everything that comes into fashion, there is an inevitable backlash once the hype passes. What Gartner would call the “Trough of Disillusionment“.

As I work with Data & Analytics teams who are seeking to embed Agile working, it’s clear one size does not fit all. Many business leaders have been trained in Scrum, Kanban or Design Sprints. But they can also face large or complex projects that struggle with this approach.


Why business games are so much more than just fun

business game

This week I had the pleasure of visiting a business game being run over 2 days for some management trainees.

These graduates came from a variety of functions, including Finance, Marketing, Sales, HR & Operations. It was a really fun day & I was very impressed with how my new associates ran the day.

But beyond the fun, I was struck by what a powerful learning experience this event provided. There were several ways that participants recognised they had learn & grown as a result. So, building on my post about leaders as educators, I thought I’d share my own reflections.


The power of pressing pause, what are you missing by going fast?


I recently had an opportunity to experience one of the benefits of pressing pause.

While presenting to over 30 Chinese non-English speaking executives, I learnt when to pause for my translator. She was excellent and taught me how long to speak before pausing for her translation. (Side note, it’s longer than you might think, as she needed context in order to translate meaning not just words).

The context of my talk was a visit by a leading Chinese insurer, to Cass Business School. To aid their executive education, that prestigious business school invited a number of leading thinkers (plus me) to present to them.


More Data Science methodology options – has much changed? (step 2 of 2)


Let’s continue our focus on Data Science methodologies. The reason for this focus is the need for more methodical delivery by many Data Science teams.

In the first post of this series, I made the case for having a Data Science methodology and shared 3 popular options. I hope you found those useful, but I’m also conscious that they are all old methodologies.

In that first post, I reviewed CRISP-DM, KDD & SEMMA methodologies. All of which were created during the heyday of Data Mining. Before the “AI winter” when exciting things were happening, but largely through using large stats packages or bespoke applications.


How Data Science teams can be more methodical (step 1 of 2)


Another tip for success with your Data Science team is to be more methodical.

By this, I mean to establish and use a consistent methodology, process or workflow. This will enable repeatable results, simpler collaboration & knowledge transfer. If it is a welldesigned methodology, it should also ensure appropriate QA stages and reduce the cost of rework.

A few different influences have had me thinking about this topic recently.