In The Know
By Rob Rowlands Research
In The KnowJul 12, 2021
Threads of Data
In todays episode I will weave a thread through concerns about the data social media apps collect, the amount of information on an application form and the helpful applicability of GDPR, all to illustrate why the purpose of information is more important than its quantity.
Getting Smarter with Data
We live in a world of smart devices designed help us do things more effectively and efficiently. But what else do we need to know to ensure we really do feel those benefits.
In this episode I ask whether smart meters can save you money and save the planet? If they are to be a means to these ends, what else do we need to be aware of to achieve those outcomes.
Let’s take a look at getting smarter with data.
https://www.robrowlands.co.uk/smart-data/
Proxy Measures
You are in the supermarket and you buy a huge cream cake. You are also on a diet. Does this mean you intend to break your dieting?
There are times when the things we want to observe and measure are difficult to get a precise angle on. From the underlying motivations of voters in the Brexit referendum to what expressed religious beliefs in the census say about Britishness, one measure is often substituted for another when we are trying to make sense of the world. We call these proxy measures.
So what is a proxy? And what does and doesn't it tell us?
Read the blog and find all the links at https://www.robrowlands.co.uk/measuring-by-proxy.
Filling the hole in the road.
When I hit a pothole in the road whilst driving I reported it to the local council and whilst the hole was filled in as a repair it was already showing signs of weakness.
When faced with a problem or a challenge, a quick fix is often employed. But how can taking a step back and gathering more information - about the context of the problem and the fit of the solution - provide a more effective and sustainable outcome?
Let's take a look.
Really Timely Data
Real time data is almost inescapable. But does it baffles more than inform? And what are the tips to using it more effectively yourself?
With examples from the world of TV sports coverage I look at what real time information we see, how helpful it is and the times when it starts to get in the way.
I will leave you with 3 questions to ask about any real time data so you can use it much more effectively.
Is "nul points" really that bad?
Strep back to Eurovision 2021, a long awaited return of the annual song contest and a great night for everyone except the UK and James Newsome. But did receiving zero points really mean his song was so bad. How might it have come about? And when can constraining choices be a helpful technique to use?
The blog is also available to read https://www.robrowlands.co.uk/constrained-choice/
Distribution
Not to be confused with parcel deliveries (Episode 5) or HGV driver shortages this episode looks at why a "one in 10" distribution isn’t as straightforward as it might first look and how understanding it can better shape our reaction.
Definitions
In this pre-summer holiday episode we look at why defintions of rain, chocolate biscuits and indoor markets matter.
The Tools of Enagagment
In this end of term episode I’ll share a story about a school, a survey and how simplicity can help secure more effective feedback.
Evaluating delivery
In this episode, what a pair of feet does and doesn’t tell you when trying to measuring the success of a parcel delivery.
Model Assumptions
In this episode we use cakes and rugby to explain what a model is, how it works and what you need to do to use one to find helpful answers.
10 Word Answers
Every 10 word answer raises a series of 10 word questions. So how can asking those questions get you to a better outcome? In this episode we talk about communities owning pubs and presidential debates.
Measured Opinion
How do we effectively use the opinions of others to make decisions? In this episode we'll talk about coffee shops, scales and the size of hotel bathrooms to find out.
www.robrowlands.co.uk/measured-opinion/
Take a sample
We can rarely know everything about a big group but in taking a sample we must recognise the limitations as well as the insights.
