Back in the early 1990s, I was working in IT at a multi-billion dollar manufacturing company. Ours was a small part of IT, separate from the mother ship. Responsible for about 2000 employees in our area, we had implemented several large projects over a two-year span; all bringing changes to the employees. I was a young IT acolyte, and I thought all change was good, great even. Why were people so grumpy? Sigh. I was so naïve.Continue reading “Square Root Of Change”
It is not always easy to tell the difference between real and fake photographs. But the pressure to get it right has never been more urgent as the amount of false political content online continues to rise. On Tuesday, Jigsaw, a company that develops cutting-edge tech and is owned by Google’s parent, unveiled a free tool that researchers said could help journalists spot doctored photographs — even ones created with the help of artificial intelligence.Tool to Help Journalists Spot Doctored Images Is Unveiled by Jigsaw – The New York Times
This is a good arms race. Fake photos and videos exist and will get harder to detect. This is the side that will fight to identify those fakes. I hope there are others.
An acquaintance of mine, who wants to stay anonymous for obvious reasons, provided me the data for the above chart. The data came from their last job hunting experience. While a successful job search — after all, they got offers — there is something very disturbing that I would like to point out.Continue reading “Ghosting job applicants”
We are flooded with data and we don’t understand most of it. While the below HBR tip of the day has specifics about communicating outside the company, I think that the basic concept — helping people understand the data — is a fundamental part of being a Business Analyst.
The standard mantra you hear is “too much data, not enough information” or “information is data made actionable”. These sayings are all getting at the fact that looking at data does not convey everything that we can learn from the data. Understand what is being looked at, understand the limitations of the data, understanding the assumptions in the data, understanding the cleanliness of the data. That is critical to having a business leverage the data they have.
But data can steer you wrong if you don’t know the information around the data.
When someone is looking at a report, is it easy to see the metadata? When someone looks at a spreadsheet or a PDF output of some sort, can they see where the data comes from and what assumptions are in place?
It is easy to simply slap a report out for the requester to get what they want. Too often, the requester and the report writer miss the fact that someone else is going to use this report six months from now and not have the same background the requester had. Or think differently from the requester.
So when writing reports or creating spreadsheets or otherwise presenting DATA that is meant to be understood, consider adding this information (automatically updated, of course) to them:
- metadata (date of data, all the parameters, specified and implied filter and sort parameters)
- Where did the data come from? Can you provide a link back to the original data for detail reports?
- What are the calculated fields and what are the calculations?
- Who is responsible for the data?
- Who do I talk to if I have questions?
- Do the field names make absolute sense to everyone looking at the report?
|Help People Understand Your Data by Making It Relatable|
|People can’t use data to make decisions if they don’t understand what the numbers mean. To help colleagues wrap their heads around a data point — how big or tiny it is, how important it should seem — compare it with something concrete and relatable. When you’re talking about lengths of time, frame your data in terms of flights between cities, TV episodes, or how long it takes to microwave a bag of popcorn — whatever your audience will know. When you’re talking about size, use places and things that are familiar to listeners. For instance, if you were trying to show a San Francisco audience what 1 million users really looks like, you might mention the San Francisco Giants baseball field, which has 41,915 seats: “Our users would fill the stadium almost 24 times.” Articulating figures this way can keep the narrative from getting lost in the numbers.|
|This tip is adapted from “3 Ways to Help People Understand What Your Data Means,” by Nancy Duarte|
As a developer, I was so tempted to put messages like this in the parts of the code that should never execute. I did a couple of times, although never this clever. I’m not up on the latest programming languages, but I imagine that it is still possible to have these places of despair. These ‘black holes’ of code where you should never go but if you do, you will never recover.Continue reading “xkcd: Unreachable State – been there, done that…”
This article was published back in the June 2005 edition of Medical Product Outsourcing magazine. As the article title says, it covers how a company’s IT infrastructure can help with its medical device design process.Continue reading “Medical Product Outsourcing – An article I wrote back in 2005”
Heard a variation of this at work the other day. Note, I have been both developer and tester in my career and fell into the above trap several times.
For those few of you that smiled at this, I strongly recommend reading the replies to this Tweet. It is hilarious. https://twitter.com/brenankeller/status/1068615953989087232?lang=en