Creative Commons License (Flickr user Sebastiaan ter Burg)

How demand-driven are you? Use this checklist to find out…..

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Creative Commons License (Flickr user Sebastiaan ter Burg)..

Note, this is part two of series. In part one I explained  how the terms “shelf-connected” and “demand-driven” have been in use for years within the supply chain community, but only recently has demand-driven value network technology  emerged and matured enough to truly be a game-changer.

Here is part two of the checklist with explanations. Questions 1-3 are here, and a full-length pdf version can be found at  Your Shelf-Connected Checklist Brief.

4.  Is my entire supply network working off a single forecast?

a. Yes

b. No

Explanation: In CPFR multiple forecasts are in play across the supply network. With DDVN however, a single statistical sales forecast is in play across the entire supply network eliminating any second guessing and misinterpretation

5. Do I have the ability to manage my forecast error with increasing effectiveness?

a. Yes

b. No

Explanation:  Although in both CPFR and DDVN use similar forecasting statistics,  in CPFR forecast error will vary-affecting supply and the ability to satisfy demand.  In DDVN however, given that the planning environment is actually part of the real time execution/transaction environment, any forecast error will be reduced over time given that replenishment cycle times and improved  inventory policies are also in play.

6.  Can I manage my replenishment on a continuous basis using a variety of optimization policies that solve for the best combination of the following?

a. CSL’s

b. Inventory

c. Warehousing

d. Distribution

e. Manufacturing

f. Transportation

Explanation: In CPFR, replenishment policies are typically batch with a precision of at best 1 to 2 days. In DDVN, replenishment is managed through a series of optimization policies that analyze statistical variances between nodes and over time are able to fine tune all process variables to create improved outcomes.

7. Can I create forecasts down to the shelf/SKU level based on daily consumer demand?

a. Yes

b. No

Explanation: In traditional systems including CPFR, forecasting is done at the aggregate level. The sheer volume of SKUs and associated decision points mean that these systems use the “peanut butter approach”, where all products are treated roughly the same despite their different demand profiles. Modern DDVN systems can automatically create granular forecasts for hundreds of millions of items at the SKU/shelf level with multiple replenishment policies based on the individual demand profile of the product. This approach would overwhelm conventional systems.

Stay tuned for the rest of the checklist in future posts, but if you want to read the whole thing now then you can download at the following link: Your Shelf-Connected Checklist Brief.


Aaron Pittman