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[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”] Introduces AI-Based System to Boost CPG Companies’ Demand Anticipation, Forecasting, a revenue growth company that launched earlier this year, introduced its Dynamic system that leverages advanced artificial intelligence to vastly improve demand anticipation and agile forecasting for CPG companies. This next-generation AI system allows enterprise demand planners to anticipate risks and opportunities in time to act and recover potential revenue.

Since Samya first caught the industry’s attention with its backing by Sequoia Capital, the company has consulted closely with more than 100 CPG demand planners to ensure that Dynamic would meet their needs and overcome the many challenges they face in accurately forecasting demand to gain the agility they need and drive revenue growth and profitability.

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“The CPG industry is facing unprecedented complexity and volatility, and that has only gotten worse amid the COVID-19 pandemic,” said Shailendra Singh, co-founder and CEO of Samya. “This costs the CPG industry as a whole more than $150 billion a year or 8 to 10% of their annual revenues as growth. Those losses can be countered with agile tools that forecast rapidly and with greater accuracy at the most granular levels.”

Dynamic, the first in a series of modules to be released by Samya, identifies where revenue growth leakages might occur in the future so a company can be truly proactive. This first module consolidates operational data, ERP data, and more than 200 continuously updated external elements to improve demand anticipation. Its unmatched agility solves the ongoing problem for demand planners of addressing anticipated risks and opportunities.

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As a cloud-based solution, Dynamic sits on top of an existing ERP system and creates forward-looking intelligence for hassle-free deployment and support. Its demand anticipation engine equips demand planners and supply chain leaders to beat MAPE (mean absolute percent error) and bias metrics that plague the CPG industry today.

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“In addition to working closely with demand planners in refining Dynamic, we have conducted proof-of-value trials with five major CPG companies,” noted Pavan Palety, co-founder and CCO. “Those trials confirmed the superior demand anticipation and forecasting that Dynamic was designed to deliver.”

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For demand planners, Dynamic addresses challenges such as:

  • Inability to isolate and account for the impact of both internal and external factors
  • Inconsistency in reconciling multi-level and multi-horizon plans
  • Slow response time and low agility not accommodating rapidly evolving demand patterns
  • Poor new product forecasting
  • Inability to anticipate and proactively respond to future exceptions
  • Weak forecasting accuracy at granular levels
  • Heavy human bias in planning and ineffective collaboration
  • Too much manual effort in managing the long tail

“Dynamic goes far beyond any demand forecasting and planning solution that exists today,” said Deepinder Dhingra, co-founder and CPO/COO. “Our advanced proprietary algorithms, AutoML technology foundation, and patent-pending approach bring the ability to incorporate a company’s internal data along with external data at scale. Demand planners can anticipate blind spots, achieve agility, and leverage the best of artificial intelligence to empower human intelligence. We enable CPG companies to recapture the 2 to 2.5 percent of potential revenue they are losing due to poor demand anticipation.”

In addition to internal factors, Dynamic incorporates more than 200 external factors such as weather, holidays, promotions, competitor pricing, and even pandemic variables to allow a planner to quantify and attribute the impact of those variables. Its artificial intelligence system overcomes human bias, enables transparency among stakeholders, and anticipates probabilities to allow planners to make the best-informed decisions.

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