In an unchanging world, with sufficient data businesses can use statistical forecasting techniques to generate an accurate forecast. Realistically, most businesses that have a demand planning process improve upon the statistical baseline forecast with the help of expert opinion.
Arkieva’s collaborative forecasting capability is designed to collect inputs from individuals who might have knowledge that can improve the quality of the statistical baseline forecast. This type of input is possible because individuals close to the customers might have information about events not reflected in the history. For example, a sales person might have knowledge of an impending shutdown at a customer’s plant or a customer winning a large government contract.
Since Arkieva’s forecast collaboration module elicits inputs from disparate user groups within the organization, security and accessibility are paramount. Arkieva has integrated data level security to ensure that each individual only has access to the segment of data they are responsible for. Also, with a wide user group users can access the collaboration module from the Arkieva application, from Excel and with a native iOS app called Sales Central.
The collaboration engine collects input from different types of users, including, but not limited to: sales reps, sales management, customers, marketing managers, product managers etc. Each of these inputs is preserved intact to maintain the integrity and track the input accuracy. Based on the accuracy, demand planners can consolidate all the forecast inputs to generate the final demand plan based on the value add (FVA) of each input.
Arkieva captures a metric called time-phase forecast value add (TPFVA), which is the forecast value add (FVA) measure over time. This metric is used to generate a final demand forecast by selectively combining the different inputs using the Adaptive Collaboration engine.
Collaborative forecasting is also integrated into the attribute based planning infrastructure of Arkieva and allows flexible level of data entry through the use of dynamic hierarchy.