I recently had the chance to present an updated version of my 7 wastes of data production talk at DataEngBytes Melbourne 2023. I think the talk was stronger this time around and I really appreciated all the great feedback from the audience. Check out the video below and the slides.
Thanks to Peter Hanssens and the DEB crew for having me as part of an impressive speaker lineup and for putting on a great event.
For the earlier versions, see the original 7 wastes post and the 2021 LAST Conference version Data mesh: a lean perspective.
Key ideas
There’s a lot of ground to cover in 30 minutes with 7 wastes from both run and build lenses, plus 5 lean principles to address the waste. The single slide below is the best summary.
The table below gives a brief description of each waste through each of run and build lens.
| Waste | Run | Build |
| Overproduction | Unused products | Unused products |
| Inventory | Stored or processed data not used | Development work in progress |
| Overprocessing | Correcting poor quality data | Working with untrusted data |
| Transportation | Replication without reproducibility | Handoffs between teams |
| Motion | Manual intervention or finishing | Context switching |
| Waiting | Delays in taking action on business events | Delays due to handoffs or feedback lead time |
| Defects | Defects introduced into data at any point | Defects introduced into processing code |
I’ll leave the summary here and encourage you to watch the video or read the slides if you want to know more.
Postscript: Inventory being a particularly pernicious waste, I have since expanded on in further in Dealing with data inventory