Fonterra is the world's leading exporter of dairy products and responsible for more than a third of international dairy trade. In New Zealand it is co-operatively owned by 11,000 New Zealand dairy farmers. The company's annual turnover is $19.5 billion with a sales volume of 2.6 million tonnes and 15,900 employees. The company benefits from modern spatial information systems in several ways:

• On the logistics side in the transport division Fonterra uses an in-house scheduling/tracking system utilising GPS (this is run out of Hamilton) that uses a road network created in MapInfo known as Genesis
• Fonterra's Strategy Team also uses MapInfo and Google Maps to inform their supply and transport strategies - the Strategy Group use data owned by the Transport/Logistics group (read-only format).

Spatial information is also important for the strategy team in communicating to area managers and the Fonterra Board. Ward and boundary information is important for Shareholders Council elections and their administration. The legislation for Fonterra also covers exclusion of farms and Fonterra uses MapInfo to ensure that the legislation is being complied with (the Clean Streams Accord, etc.). The strategic analysis requires spatial tools - a task that takes 2 minutes using spatial tools would take 2 weeks without electronic data and the ability to interact with that data in a spatial format.

Benefits in terms of accelerating individual tasks in strategy and planning are clearly important but their financial impact on the company is difficult to assess. It is however also noteworthy that Fonterra staff reportedly enjoy using MapInfo which could in turn enhance productivity or assist with staff retention in the longer term.

In terms of more readily measurable productivity benefits from spatial technologies, the transport/logistics benefits were highlighted. Fonterra collects from up to 10,500 farms each day, transporting milk to 26 production facilities - clearly a monumental task and one in which spatial information is already known to have the ability to make significant productivity impacts (as discussed in Section 2.10, which deals more specifically with various transport benefits). This was confirmed in discussion with Fonterra, as outlined below.

When Fonterra first formed in 2001 they used an early spatial capability - a point to point system with a road overlay for scheduling known as the Computer Aided Milk Scheduling (CASH) system. This was not centralised and data was transferred through radio or small devices that were used by the drivers' team leaders for manual input.

The modern spatially enabled system used by Fonterra for the last two years involves live scheduling, dispatching and tracking of vehicles/loads. The run sheet is delivered electronically to an in-cab system. Units in trucks log location every 7.5 minutes (the limit set by communications technology, not spatial technology), and identify when trucks are at farm. Tags identify the farm and a flow metre logs the pickup quantity. A significant investment was required to get this up and running - for example, change in vat piping, purchase of in-cab units, software, and so on. Five staff at Fonterra were involved in the development of Genesis, and the success of the project also relied on significant user input.

The system is dynamic in the sense that vehicles can be rerouted almost instantly, taking into account a range of factors to identify the optimal route. Given the ability to track driver location in real time it allows, for example, directions to be given to drivers during night-time pick up when visibility may be low. The system also takes account of various constraints such as the ability to turn out of driveways (using Google Earth to identify tanker turn restrictions), bridge weight limits, and scheduled pick-up time.

For Fonterra, all of this has led to an ability to reduce or redeploy schedule and dispatch staff,[1] as well as enabling a reduction in vehicles on the road. These changes have influenced the productivity shock modelling for the current report - efficiencies of 20 to 50 per cent were achieved in specific areas. Spread across the company as a whole, the productivity gains from spatially enabled transport logistics at Fonterra could be in the region of 0.25 per cent labour productivity, with additional savings from multi-factor productivity.

Figure 21: Location of all Fonterra trucks at a point in time

Development of the spatial platform for this application also means there is now spatial data for Fonterra suppliers in spatial format/context, and it is used by other parts of the business (strategy, property, production planning) - whilst these parts of the organisation were not instrumental in creating the system/capability they are now increasingly starting to consider how they can build on the platform for their own purposes, e.g., forecasting milk production based on climate and grass growth. This is a typical example of a case where initial innovation is now providing demonstration effects that will see incremental adoption and growth of acceptance of spatial information through the organisation.

A number of other aspects of the Fonterra experience are relevant for this report. Fonterra reported to be engaged in ongoing development and that consultants from the 'core' spatial industry were providing excellent service, including developing solutions for dealing with low quality cadastral data. Whilst there was significant customisation of the product, the basic equipment (in cab GPS/dispatching, GIS integration) is off the shelf.

Figure 22: Location of vahicles and single vehicle detail

Forward looking issues

Fonterra is examining the possibility of using better altitude data. At present the approach is to start at the top of the hill and work down to avoid hauling milk up hill.  Fonterra has elevation data for each supplier but currently has to assume straight line elevation change between suppliers. A high quality digital elevation model would also be useful for understanding logistics implications of bringing on new suppliers or identifying areas that could be developed.

An issue with merging public (cadastral) and Fonterra (highly accurate) data was noted but the company has generally managed to find work-arounds.

Barriers have been technical - the business case was easy to establish (perhaps since there have been several iterations of computer based tracking prior to GPS enabled Genesis).  Finally, it was noted that better mobile data transmission rates would be helpful.

This case study has been taken from the Spatial Information in the New Zealand Economy - Realising Productivity Gains report, August 2009.

References

[1]    Numbers provided but confidential. These savings have occurred in part as a result of centralising scheduling/dispatch operations. It is not possible to do this without spatial data and GIS technology to integrate data effectively.