:o9 Digital Brain for Consumer Durables

Makes pioneering water and housing products that solve everyday, real-life challenges, improving home quality.

This customer experienced demand planning challenges
related to a low accuracy forecast and great dependence on Excel spreadsheets.

Sustainability Impact

Reduction of inventory.

Business Scope Challenges

Manual Number Crunching

The company depended greatly on manual exercises of demand planners, by which they copied data from sheets and manipulated the data to obtain demand scenarios. This resulted in time-constraints when reacting quickly to changes in demand.

Opportunity

With o9, they can still use Excel files through o9’s highly differentiated Connected Excel UI, but no longer need to manually move data. By leveraging o9’s unique integrated platform, they won back valuable time.

Forecasting

The forecast accuracy was low and predominantly only lagging indicators were used in the forecasting process.

Opportunity

With o9, the company was able to incorporate
internal and external drivers of demand
(macro indicators such as GDP) into o9’s
highly differentiated ML forecasting capabilities to help improve their accuracy.

Planning in Silos

The planning processes varied widely across countries, with a lack of a single process or overview.

Opportunity

With o9, the company will get the unique capability of connecting all planning processes across time horizons on a single integrated, cloud-native platform.

Value Delivery

Key Functionalities Implemented

The o9 Enterprise Knowledge Graph was used to build demand knowledge models that are incorporating leading indicators of sell-out (trade promotions and marketing initiatives). o9 leveraged its open architecture by using best-in-class algorithms from R and Python to get to an optimal forecast.

Systems Replaced

Excel.

Customer Benefits

Success Factors — 3 reasons why o9 was selected 

  1. o9’s highly differentiated Enterprise Knowledge Graph allows leading indicators of demand to be incorporated and leveraged those indicators for more accurate forecasts.
  2. Reduced manual efforts.
  3. o9’s ML capability for demand forecasting.

KPI Impacted

  1. Improved demand planning forecast accuracy, enhancing capability to fulfill impact orders.
  2. Improvement in planner productivity.
  3. Sell-in sell-out conversion improvement, through better POS data usage, increasing business, and reducing stock-outs.

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