Treasure 104 – Agility, Data Science, Effectuation

How does the classic organisational tanker become an agile fleet association? How do you become a Citizen Data Scientist? What is the affordable loss? The nuggets in treasure 104 are real heavyweights and have the potential for significant change in your company.

The Masters Of Transformation Podcast by Ingo Stoll is one of my favourite podcasts and has been in treasures several times, e.g. in treasure 41 on the subject of complexity. I like the manifold stories about changes in people and organizations. When episode 90 appeared in my list of new episodes, I thought to myself “Oh no, not another agile framework”. Fortunately, FLEAT is not one of those frameworks that is being put over an existing organization with dozens of rules. Rather, it comes with an easily understandable visual language. One speaks of rafts and rowing boats. The episode with Uwe Habicher and Torsten Schaar by Haufe is therefore predestined as Nugget #1 in a treasure on CompanyPirate.
Interesting are the different scaling phases. Most of all I like the activation phase. On the one hand, this “phase” is almost not existent in many companies. People may just be talking about dreams. People prefer not to talk about nightmares and threats. On the other hand, it fits in well with my mission as a company pirate – to inspire people in companies. So if you need support during the activation phase, please contact me .
It’s good that the teams on rafts and steamboats can organize themselves in a way that suits their business best. Also the composition of the teams is not fixed. If someone gets out at the end of the raft phase and hires on another raft, that is completely legitimate. At first glance, FLEAT seems to be real entrepreneurship instead of a pseudo-startup program in the corporation. This of course includes failure, as the following quote makes clear:

“If someone goes down with a raft, then the organization has invested in his/her training.

As such I would like to take someone on my raft who already knows some rapids. I’m looking forward to more reports about experiences with FLEAT. (86 min, audio, German)

090: FLEAT – An agile framework for the organization

Artificial intelligence, big data, neural networks – these terms are constantly coming your way today. Nugget #2 is a long-read by Oleksii Kharkovyna, which gives you access to the topic. Not everyone has to become a data scientist. To use the potential of Data Science you also need Citizen Data Scientists, who can perform analytical tasks themselves and easily create models. What is the potential for your company? Here are three examples.

  1. Analysis of your company’s sales data – What is the sales trend in which region? Which product is in demand how often? What do delivery times look like? From which product are there how many returns? Which products are viewed on your homepage by whom and how often? In the first step you can process and visualize the different data (see step 4). This results in first insights for the improvement of sales. With the help of machine learning you can automate this process and even generate forecasts.
  2. The same also works for production processes. How does the temperature develop in pumps? What is the course of vibration in motors? What is the color deviation of a product? This data can also be used to optimize processes and generate predictions for maintenance. Spare parts are ordered in good time and rejects are avoided. Cash money for your company!
  3. Machine learning can also be applied to the product and thus generate added value for the customer. There are manifold examples – language assistants, intelligent thermostats, vacuum cleaner robots.

Unfortunately there is a lot of ignorance and fear around the topic of artificial intelligence. Some activities an algorithm can do better today, some maybe in a few years. Will an algorithm take over some or all of your activities in the future? No reason for me to bust your head in the sand. Maybe this article is the beginning of your way to becoming a Citizen Data Scientist? Thanks to my reader Christian Dremel for recommending this article. (12 min, text, English)

A Beginner’s Guide To Data Science

The previous treasures often dealt with the topic of decisions. I briefly mentioned the principle of effectuation. Nugget #3 by Heiko Bartlog is therefore just right. In his article the five principles of Effectuation are explained again briefly and concisely.
The principle of affordable loss is unknown in many companies. How much time is used in your company for Business Cases or Return-of-Invest calculations? Assuming a team of five people spends only half a week working. At an hourly rate of 100 €, the pure working time already costs 10,000 €. Instead of a business case, you could consider it as an affordable loss and spend it on an MVP. Usually it takes 2-3 weeks until the sponsor has time for the presentation of the business case. If you calculate a “cost of delay” for this time, the affordable loss could be even higher.
Do you feel like thinking more about the five principles? My article about misfits matches the principle “Useful coincidences”. I put the principle “valuable partnerships” on the Creative Backlog for own contributions.
PS: If you prefer to watch a video instead of reading, treasure 47 contains the TED talk by Saras D. Sarasvathy, the founder of Effectuation. (5 min, text, German)


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