With all the challenges and unpredictability in business today, it’s no wonder those of you in enterprise operations are excited about new developments in technology that can help you prepare for what’s coming next. Current conditions are affected not just by customer seasonal demand but carry the added burden of weather, economic and news cyclesexponential expansion due to globalization, new and constantly changing rules and regulations, and ongoing competitive feature and pricing development. When you add the recent changes in constrained business environment due to the COVID-19 pandemic, it’s not hard to see that there needs to be an easier way to flexibly prepare for any conditions, at any time. This is where forecasting becomes the central point of attention. 

Today’s Challenges in Forecasting 

With the advent of artificial intelligence (AI) and machine learning (ML)you now have the ability to model and predict using any available data to describe your current business situation, going well beyond just historical observations of sales. This is a huge benefitbut it’s still in its infancy.  

 In many of the software packages today, the models are constrained to prepackaged solutions, restricting data and limiting the ability to gain the full benefit of ML. When the software program is also constrained by scale or platform, or compromised on frequency or granularity, the forecast may not represent elements integral to business decisions. Much of the speed needed to produce accurate decisions is dependent on the programs’ ease of use and features. These are all factors in delivering the right forecast at the right time. 

The Value of Scalability 

How can AI-based forecasting and the ability to process data at massive scale help you achieve revenue and agility objectives? 

According to McKinsey Digital, AI-powered forecasting can reduce errors by 30 to 50% in supply chain networks. The improved accuracy can provide up to a 65% reduction in lost sales due to inventory out-of-stock situations and decrease warehousing costs around 10 to 40%. The estimated impact of AI can be between $1.2T and $2T in manufacturing and supply chain planning. 

Scalability in forecasting gives you the ability to 

  • Ensure your demand predictions take into account not just the promotional lift of this item, but the impact on other items and the impact of competitors marketing and pricing changes on your products. 
  • Help your planners know how much of what raw materials will be needed at a daily/hourly level at each facility – improving materials distribution will cut costs of duplicate orders or eliminate emergency resupplies.
  • Improve customer relationships by avoiding stockouts or supplying products on-demand, based on accurate forecasting including key information from your customers such as inventory, promotional calendars and more. 
  • Create forecasts for products or locations that never existed before in your supply chain. 
  • Specific domains such as logistics suffer constant disruptions. Data on weather, driver status, traffic patterns and sensors is growing at an unprecedented rate but connecting both internal and external data produces highly accurate demand forecasting, for instance to accurately forecast pickup and delivery commitments. 
  • Retail businesses that can process billions of items and SKUs in real-time regularly for assortment planning and pricing will stay ahead of fast-changing trends, such as the effects of consumer choice, shifting buying to online channels and a myriad of other changes impacting the retail industry. 
  • Forecast new business models, digital inventory, mobile app utilization patterns, support center needsby language and topic. 
  • With IoT sensors, many of the silos that often arise between production and supply chain can be eliminated by producing realtime data, enabling analysts across departments to adjust quickly through the comparison of primary and secondary data that highlights any gaps or trends that may be occurring 
  • Be able to forecast workforce needs or shifts during continuously changing periods and prepare for transitions to new working environments and resource requirements 

Preparing for Next-Generation Forecasting 

A real-time forecasting system is only as good as the data it can consume and analyze. If your forecasting can’t efficiently ingest and process billions of items and continuously changing data, it won’t be able to provide accurate results. 

 Applying smart and efficient AI/ML solutions built for the cloud give your teams the opportunity to address scalability, flexibility and cost, while integrating with existing systems of record. Cloudnative solutions bring the ability to manage massive data with the elasticity of scale to create forecasts at the granularity you need, in the time that you need it. 

 Your forecasting needs to adapt and change with business conditions in an ongoing way that can process new inputs and address new concepts such as intent data, all while continuously ingesting larger and larger amounts of real-time data. 

How to Build Greater Business Resilience and Results through AI/ML-based Forecasting

AI and ML in forecasting can help address a number of valuable areas to improve productivity, reduce time and manual effort, reduce costs and increase competitive differentiation. These are some examples of where AI/ML-based forecasting have been proven to be invaluable to organizations: 

  • Forecast New Products Faster 
  • Eliminate traditional manual or semi-manual methods using a “like” item
  • Leverage More Data  
  • Apply sentiment, weather, price, promotion, customer information, etc. 
  • Scalability for Greater Insights 
  • Forecast at a lower level of granularity, such as from monthly sales to daily sales, or from product category down to SKU 
  • Real-time Forecasting 
  • Ingest enormous amounts of information in real-time to produce forecasts more often, and closer to need 

Applying the use of intelligent cloud analytics across your supply chain, merchandising, marketing, materials, product, billing, document management, or workforce planning, your organization can prepare for any changes through AI/ML-based forecasting. 

A Unique Approach

With years of experience and thousands of manhours of analytics expertise, Core Compete is uniquely able to leverage the cloud to create AI/ML-based solutions for forecasting, in-store testing, and automated processing across mega-sized, real-time data sets. With a unique “Analytics Innovation Studio” approach to helping you find the right solution fit for your organization, Core Compete’s expert team quickly comprehends your need, defines a solution, and within weeks gives you the ability to meet any business challenge through the advantages of modern, innovative and efficient technology 

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