Intelligent Category Growth Forecasting for a U.S. Cosmetics Company

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Drupal\dxpr_builder\Service\DxprBuilderService->loadCmsElement(Array, '', Array, Object) (Line: 1250)
Drupal\dxpr_builder\Service\DxprBuilderService->parseDocumentForCmsElements(Object, Array) (Line: 1085)
Drupal\dxpr_builder\Service\DxprBuilderService->parseForContent(Array, ) (Line: 333)
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Drupal\dxpr_builder\Plugin\Field\FieldFormatter\DxprBuilderFormatter->viewElements(Object, 'en') (Line: 91)
Drupal\Core\Field\FormatterBase->view(Object, 'en') (Line: 268)
Drupal\Core\Entity\Entity\EntityViewDisplay->buildMultiple(Array) (Line: 339)
Drupal\Core\Entity\EntityViewBuilder->buildComponents(Array, Array, Array, 'full') (Line: 281)
Drupal\Core\Entity\EntityViewBuilder->buildMultiple(Array) (Line: 36)
Drupal\block_content\BlockContentViewBuilder->viewMultiple(Array, 'full', NULL) (Line: 24)
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call_user_func_array('Drupal\block\BlockViewBuilder::preRender', Array) (Line: 111)
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Drupal\Core\Render\Renderer->doRender(Array, ) (Line: 240)
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Twig\Template->render(Array) (Line: 38)
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twig_render_template('themes/custom/visionet/templates/page.html.twig', Array) (Line: 348)
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Drupal\Core\Render\Renderer->doRender(Array, ) (Line: 240)
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Twig\Template->render(Array) (Line: 38)
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twig_render_template('themes/custom/visionet/templates/layout/html.html.twig', Array) (Line: 348)
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Drupal\Core\Render\Renderer->executeInRenderContext(Object, Object) (Line: 153)
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A multinational beauty company was facing difficulties in devising scientific method for forecasting and strategic planning. Visionet developed a accurate predictive forecasting pipeline accommodative of managing all data sources and external factors, lashed with capability to handle future challenges. The resulting forecasting pipelines enabled data-driven decision-making capabilities impacting product innovation, opening new markets, and supply chain planning.

Challenge:

The client's innovation team relied on intuition and assumptions to project the market outlook. They needed a digital solution to build a predictive forecasting pipeline, which could handle complex data from internal and external sources, across different product categories and sales channels. The client required a flexible platform that allowed for need-based changes and addition and deliver accurate forecasts and data-driven insights to modernize their strategic planning.

Solution:

Visionet proposed a platform fabric for forecasting pipelines addressing data variety complexities. To assure accurate forecasts, it used three forecasting model pipelines - Multivariate Model, Univariate Model, and Regressor Search Model - and a smart AI search algorithm. The platform leveraged Visionet's data engineering expertise and data toolkit to harmonize and transform data, and delivered forecasts at multiple granular levels, while addressing COVID data anomalies and recovery dynamics. The resulting data-driven decision-making capabilities enabled the client to achieve their desired business goals efficiently.

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Intelligent Category Growth Forecasting for an American Cosmetics Company

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Challenge:

Solution:

Services

Products

Quick Links

Contact