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Predictive Analytics

  • Kimberly-Clark Empowers Front-End Innovation

    Like many consumer goods companies, one of Kimberly-Clarks biggest challenges was creating high-value ideas and concepts to grow new product revenue. The quantity of ideas was not the problem it was the quality. Heres a look inside the companys multi-year journey to improve results from innovation efforts.

  • The Evolution of Sales & Marketing Planning

    Marketing, pricing and trade promotion activities are critical to the success of consumer products companies. The stakes are high as companies spend billions of dollars trying to grow their business. Those who can better understand, plan and predict are winning, those who cant move toward extinction.
  • Pacific Natural Foods Masters TPM in the Midmarket

    Pacific Natural Foods makes gross margin gains with aggressive trade spend strategy.
  • Tips for Driving More Value with Innovation

    Todays consumer packaged goods companies face extreme demands on innovation and market responsiveness, but they must also quickly navigate a tangled web of product compliance mandates in order to protect profitability. Here, two industry experts share their proven tips for improving the velocity of value creation within your organization.

  • Sunny Delight Reduces Fuel Costs and Emissions

    Sunny Delight uses clean energy trucks to reduce fuel costs and emissions with a third-party logistics company.

  • Oldcastle Improves Supply Chain Visibility

    Comprehensive analytics from Vision Chain are expected to provide Oldcastle with sales and supply chain visibility for actionable insights.

  • IBM to Acquire Tealeaf Technology

    With this agreement, IBM extends its Smarter Commerce initiative by adding qualitative analytics capabilities that aim to provide real-time and automated insights into online customer buying experiences across online and mobile devices.

  • Data, Data, Everywhere

    Manufacturers accumulate lots of data from their supply chains. Were not suggesting that they need to use all this data right away; but many are using very little of it to improve their forecasts. By taking some small first steps with their data, manufacturers can make some giant leaps in their forecasting.

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