5 Dos And Don'ts For Using Demand Data - InformationWeek
IoT
IoT
Software // Information Management
News
2/26/2009
06:30 PM
Connect Directly
Google+
LinkedIn
Twitter
RSS
E-Mail
50%
50%
RELATED EVENTS
[Cyberattacks] Using Data as Your First Line of Defense
Aug 10, 2017
Attend this webinar to learn how you can determine which threats pose the greatest danger to your ...Read More>>

5 Dos And Don'ts For Using Demand Data

Get these right before tapping point-of-sale for supply chain changes.

BEST PRACTICES

DON'T Overanalyze factors you can't control
If the root cause of a problem is controlled by others, such as distributors or retailers, determine whether you can change the business process or behavior. Demand-signal analysis can easily spot poor promotional execution, for instance, but it doesn't help a manufacturer if its field staff can't work with retail managers to straighten out stocking and merchandising errors.

DO Pick the big opportunities
Supply chain optimization, logistics planning, retail category management, promotional execution, shrinkage control, stock-out forecasting--these all are good prospects to improve through demand-signal analysis. But start with the problems that can deliver the biggest payoffs. That typically means improving promotion performance and reducing stock-outs.

DON'T Reinvent the wheel
Collecting, normalizing, and cleansing high-volume demand-signal data is costly and time consuming, particularly when a manufacturer is dealing with multiple retailers, all of which likely send data in different formats. Look for data networks and aggregation specialists that work with key retailers and leading manufacturers. Wal-Mart's Retail Link, Retail Solutions' Demand Signal Repository, and Vision Chain's Demand Driven Supply Network are leading sources of demand data.

DO Use demand data to spot "phantom inventory"
Consider this scenario: Shipment data suggests an item should be in stock, but demand-signal data shows it's not selling. Is the product a dud, or is it actually out of stock? Stocking errors, breakage, theft, and bad scans can lead to "phantom inventory" that's really not in the store. Some analytics software can compare sales histories with demand data to spot suspect conditions.

DON'T Set off false alarms
Demand-signal analysis can be used to predict and prevent problems, but watch out for false alerts. Say a manufacturer's order history shows suntan lotion should be selling at a store in Florida, but point-of-sale data shows no scans. That may not be a stock-out situation. Retail Solutions does demographic or geospecific store cluster analysis to spot factors such as bad weather. Make sure your approach includes reality checks before triggering alerts or, worse, automatic replenishment.

Continue to the sidebar:
Software Giants Join Specialists In Demand Management

Return to the main story:
In A Down Economy, Companies Turn To Real-Time Analytics To Track Demand

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
How Enterprises Are Attacking the IT Security Enterprise
How Enterprises Are Attacking the IT Security Enterprise
To learn more about what organizations are doing to tackle attacks and threats we surveyed a group of 300 IT and infosec professionals to find out what their biggest IT security challenges are and what they're doing to defend against today's threats. Download the report to see what they're saying.
Register for InformationWeek Newsletters
White Papers
Current Issue
IT Strategies to Conquer the Cloud
Chances are your organization is adopting cloud computing in one way or another -- or in multiple ways. Understanding the skills you need and how cloud affects IT operations and networking will help you adapt.
Video
Slideshows
Twitter Feed
Sponsored Live Streaming Video
Everything You've Been Told About Mobility Is Wrong
Attend this video symposium with Sean Wisdom, Global Director of Mobility Solutions, and learn about how you can harness powerful new products to mobilize your business potential.
Flash Poll