CAMM (Customer Address Master Mapper)
One of the problems that faces the 3PL industry, is the integration of customer information from the different principles/suppliers. In an ideal world, the principles would all have the same customer numbers for their clients. Obviously this is not the case, so the next best thing would be for each customer to have the same name and address information. Again this is not the case. So, when invoices come through for the day's deliveries, several of them may have common customers, without the despatch staff or their scheduling software (like FLO) realising it.
As an example, “Pick `n Pay Morningside” may be a customer for principle “X” and principle “Y”. Compare the following customer data for each principle:
Since the customer name and code are different, they appear as two different customers and the address information differs enough that one may think their locations are different too.
When FLO receives these invoices, two different customers and delivery points are created. Each invoice may then be scheduled on different vehicles, even though they are actually for the same store.
This is a simplistic example, but imagine how the problem compounds when there are at least 4 principles involved with say, 200 invoices per day! The scheduling setup then becomes quite tedious because the user has to manually link all these common delivery points inside FLO. This can quite easily be done, but it is time-consuming.
That's where the Customer Address Master Matcher (CAMM) comes in. CAMM's intention is to identify these “common” customers and link them to a “Master Customer”. FLO can then schedule them properly as a single customer.
The way in which CAMM works is quite simple. Firstly, a set of master customers is generated against which all matching will be done. The master customers are associated with a chain store where applicable. Several spellings can be associated with each chain, to aid the matching engine, e.g. “PnP”, “Pick & Pay”, etc. for “Pick 'n Pay”. The customer on the invoice is matched against the chains to attempt to find the relevant chain. Once this is done, the address information is matched against all stores belonging to this chain to find the correct store.
The following screenshot demonstrates how the user has given as many possibilities for the spelling of the chain name “Pick 'n Pay”, with differentiations between the types of chain stores as well, i.e. “Hypermarkets”, “Family Stores” and “Supermarkets”.
If the store does not belong to a chain, the customer's name and address information is matched against all non-chain master customers. If, in either case, a single match is not found, CAMM displays a message on the interface, which indicates where the matching failed. The user then has the choice of creating a new master customer (directly from the interface) or selecting the correct master customer from the existing list. Once invoices have been matched to master customers, the invoices are exported in the correct format for FLO to import.
Automatic matches (made by the matching engine), as well as manual matches (made by the user), are stored in the database so that the next time invoices are imported with the same incoming customer numbers, the match is made immediately without having to go though the matching engine. Not only does this save any previous changes, but it also speeds up the whole process.
From a data management point of view, CAMM allows the user to control many other aspects of the master customers, so that the information is stored in a central repository. Any invoices that are then matched with this master customer will automatically inherit its business rules. Examples of this centrally-managed data include delivery windows and nominated delivery days (NDD's). In the screen shot, the depicted customer receives deliveries only on Mon, Wed, Thu and Fri. Wed and Fri delivery windows are different from Mon and Thu windows.
The following screenshot demonstrates how the user has entered delivery windows for each day that the customer accepts deliveries.
Setting up new master customers is easy, with the associated wizard. The user selects a chain (where applicable) and then creates a new delivery point (through another easy-to-use wizard) or selects one from the list of existing delivery points. Delivery points are set up by selecting a postcode, suburb and street from a pull-down. CAMM then automatically geocodes this new delivery point at the lowest level possible, i.e. street first, otherwise suburb, then postcode. There is no need for the user to have to geocode the delivery point on a map.
In summary, CAMM is designed to help 3PL clients who need to merge invoices from several suppliers/principles. It enables the client to have tighter control over the data that FLO uses to schedule deliveries and streamlines the process of identifying common deliveries.
