Chainalytics’ Demand Planning Intelligence Consortium (DPiC) analyzes the underlying drivers of demand uncertainty to help member organizations improve demand planning and ultimately supply chain performance.
An organization’s demand planning forecast accuracy directly influences working capital requirements, inventory strategies, safety stock levels, and overall operating costs surrounding the total cost-to-deliver. Beyond financial performance impacts, customer service levels are also directly impacted by forecast accuracy as well as management’s expectations for that product group’s availability and delivery. Avoiding “stock outages” by accurately forecasting product availability at the right time, in the right quantity, and in the right location can be critical to maintaining, or even gaining a competitive advantage in today’s market.
While a product’s forecast accuracy won’t be 100% accurate, understanding exactly where that demand uncertainty is most probable can be essential for an organization looking to positively impact profitability and customer satisfaction. By knowing exactly how much error is reasonable, and how much inaccuracy you can afford is a more effective approach.
What does Chainalytics’ Demand Planning Intelligence Consortium do?
Chainalytics’ proprietary DPiC empowers executives and owners to rapidly align their performance expectations, targets, improvement initiatives and resource allocation plans. DPiC enables planning teams to directly identify the source of forecast errors, effectively manage by exception, and pursue necessary corrections efficiently. The DPiC approach provides a robust set of descriptive and predictive tools that allow members to compare and analyze forecast accuracy and bias within a consortium, (member-based benchmarking organization) – all while keeping actual sales and forecast accuracy data completely confidential for each member company.
The DPiC is technology-agnostic and uses readily available, standard data to enable quick and easy participation. Using granular data and a standardized methodology, the DPiC takes a precise snapshot of each firm’s actual forecast accuracy and bias, then normalizes those metrics against portfolio forecastability and the rest of the DPiC dataset. The analyses and models clearly exhibit the influence of individual demand patterns, product phases, channel characteristics, and policies on an organization’s ability to forecast demand efficiently.
DPIC provides quantitative visibility into exactly:
By employing a superior, proprietary model-based benchmarking approach using item-location level, final consensus forecast data and transactional shipment data, the resulting forecast accuracy and bias models provided by DPiC quantitatively capture the combined effect of specific demand, product, and network characteristics to enable teams to understand exactly where more accurate forecast predictions are achievable. Together with best practice benchmarking, comparative market analysis and portfolio intelligence, DPiC empirically answers all-too common questions that often have a bottom-line impact on both downstream and upstream supply chain operations. With the help of data-visualizations and interactive analytic dashboards, DPiC efficiently communicates these various impacts in simple to understand terms beyond the demand planning team.
(DPiC) enables organizations globally to:
You cannot improve what you do not measure.
Join the DPiC today so your company can gain a better understanding and higher predictability as to how your supply chain will respond to the evolution of your business and maintain your competitive advantage in the market.
For more information on Chainalytics’ Demand Planning Intelligence Consortium or to schedule a live demo, simply email us at email@example.com