The ability to see way back into the sup- ply chain enables Henkel to calculate the cost-to-serve per item. “We know which production line and packag- ing line each bottle of detergent comes from. We know the efficiency of those lines and even how much energy and water they have used. Combined with information about the logistics costs, we can then precisely calculate how much it costs to get a certain product to a cus- tomer,” says Weber. Henkel uses that data to model scenarios and to substan- tiate strategic and tactical decisions. “If we want to add a new warehouse to our distribution network or want to move the production of an item to another plant, we can immediately see how that will impact on the cost-to-serve.”
In-house development
According to Weber, no standard soft- ware offers the visibility that Henkel needs. “That’s why we’ve developed these tools ourselves to be able to ana- lyse data on the Cloudera platform and to visualize it on dashboards in Tableau. Because everyone has a different level of responsibility, they get to see differ- ent data. Very few people need visibility of the end-to-end supply chain,” states Weber. “That doesn’t mean that we don’t use standard tools. There are lots of smart solutions available nowadays, such as demand sensing by E2Open. That’s a software vendor with the right knowledge and experience in a relevant area for us.” Henkel has limited itself to the inbound supply chain just beyond the tier one supplier. “That might change if we’re expected to provide insight into the eco- logical footprint of our entire supply chain. In that case it will also be neces- sary to know the CO2
emissions and 32
energy and water consumption of our tier two and tier three suppliers.” Henkel is currently working on creat- ing visibility at not only SKU level but also item level. The longer-term aim is for each product to have a unique code.
Weber: “Then we can scan the code of the product to see at a glance which production line it has been made on, in which factory. In the future we’ll even be able to give consumers insight into the origin of the product, although
that’s not our main aim. Various sys- tems in Europe are already capable of scanning these codes and we’ll be extending that over the coming years.”
Data crawler in the cloud
Alpro is currently exploring how it can improve the visibility of its internal sup- ply chain. The company, which became part of Danone a year ago, produces plant-based alternatives to dairy prod- ucts, e.g. soya drinks, hazelnut drinks and almond drinks. Its three factories (in France, Belgium and the UK) run on SAP R3, and SAP APO is used for fore- casting. For things like production plan- ning, Alpro uses a solution from OM Partners. “SAP records a huge amount of data, but we don’t always manage to extract it and convert it into useful infor- mation,” says Peter Decroos, Interna- tional Planning Process and Tools Man- ager at Alpro.
The company immediately achieved interesting results with its first pilot, conducted with a tool by Bluecrux – a Belgian consultancy firm that has its own software platform which Decroos refers to as ‘LightsOutPlanning’. “We did a dump of all the material move- ments recorded by SAP over the course of two years. We put that data in the LightsOutPlanning cloud and then let the data crawler loose on it. Using that transactional data alone, the tool suc- ceeded in mapping the supply chain network, creating a digital twin and calculating
parameters,”
relevant explains
supply Decroos.
chain “That
immediately revealed some interesting insights.”
One example was the period of time that certain product groups such as the drinks have to be kept in quarantine. Decroos: “The products must be pack- aged in sterile conditions. To assure this, many of our products go into quar- antine. We can’t release and ship a prod- uct until it has been approved by the quality department. This step is regis- tered in SAP, as is the release of the pal-
SUPPLY CHAIN MOVEMENT, No.31, Q4 2018
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48
