Reminder about 5S
The 5S stand for the basic principles allowing to build and maintain an efficient, functional and safe
work environment, ruled with simple, yet effective rules. The 5S acronym is made of five Japanese words starting
- in western transcriptions - with the letter "S" ; Seiri, Seiton, Seiso, Seiketsu et Shitsuke..
5S, as many other concepts, methods and tools originated in industrial workshops.
Their proven success and compatibility with other types of activities allow them to spread to offices next to
production, before spreading in all kind of activities like services and administration.
These principles are universal and suitable to factories, workshops, shops, warehouses, offices, restaurant kitchen or even
in one's own private household!
Basically, 5S foster keeping only the usable, setting things in order, and cleanliness which are
the 3 first Steps. The fourth S defines the housekeeping rules to keep the first 3S alive,
and the last but not least S strives continuous improvement.
Transposition into software
In the physical world, what is useless and jams the work area, what can lead to errors and mistakes,
confusions and even accidents is hunted down to render the work environment functional, efficient and safe.
Cleaning and keeping the area tidy is a way to favor quality of work and easy detection of abnormalities.
The same approach can be used for electronic files and data:
Sorting data, files and documents which are packed into the system, then suppress the
useless and obsolete ones to regain storage space
Arrange the remaining (useful) data wisely, using common sense, to favor their sharing
and quick intuitive retrieving. Keep only up-to-date data and documents handy, archive and store "remotely"
the least, not so often used once.
"Cleanse" frequently contents of folders, mail boxes and files. Beyond cleansing,
try to eliminate sources of pollution, like spam mails, multiples copies, etc. Cleansing encompasses also regular backups.
Set rules on a consensus, keep rules simple and efficient so that everyone sticks to
that discipline
"Audit" periodicaly your systems to check the rules are applied, measure system performance
(response time, number of duplicates...) and readjust rules according to progress.
A computer is made to arrange, sort and set data in order, it basically uses rules and principles to do it.
The problem is, a computer will do it with same efficiency with old, obsolete, incomplete data and even corrupt files.
If it knows perfectly to sort masses of data according to multiple criteria, it is not capable to state about data
usefulness, not always about their validity or usefulness. Cleaning and maintenance of contents remain all human operations.
Talking about soft data, the word "maintenance" may sound strange, yet it is in neglecting data hygiene
the risk lay.
Data maintenance
Logistic data are a large and complex set of data, rules and information necessary for the
Supply Chain to work. For granting a physical delivery from suppliers to customers,
lots of data are necessary for purchasing, sourcing, supplying, manufacturing and deliver. These data are linked to others
like inventories, technical data (bill of material, for instance).
Production needs a planning and work structure files to give
guidance and information how to manufacture what with what and when, in which sequence and order. Production itself
provides multiple documents and data about schedules, achievements and consumption of material and parts.
Shipping are based on shipment plannings, inventories and logistics data.
Billing uses also data about shipment and payment conditions.
The amount of data raises extremely fast, according to the number of suppliers, products and clients.
The number of possible malfunctions linked to false, incomplete or missing data raises accordingly, but
furthermore may combine through the links and shared files among systems and applications.
Three emblematic examples
Here are three real examples of risks for the business, related to poor data hygiene:
This company fails most often to deliver the products to its customers on time, because of
thermal treatment, acknowledged as a bottleneck. However, thanks to a raw material specifications
change for some products, thermal treatment is no more required. If this process still goes on for every product, stealing
direly needed capacity and nagging on profit, it is because the technical data in work package haven't been updated
until now.
Production suffers stop-and-go because of material shortage. However, the company is overburdened
with inventories, yet it seems what is needed is never available. In fact, stock taking results and inventories figures
are badly reported, the computer works on corrupt data.
After surprisingly loosing a big contract with a long known client, the salesmen find out that
deliveries do not match the new conditions imposed by their client new just-in-time organization.
The customer file was not updated with this vital information.
As these three examples demonstrate, data maintenance should be understood as swift updating
after any change, but also as periodical validity and reasonableness (true-seeming) check.
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