Use cases

Energy for Utilities & Commercials

Forecast demand and renewable production
Power market pricing & Purchase Optimisation
SmartGrids and Energy efficiency Management

Retail & supply chain

Automate demand forecast, sell-in/out
In-Store Operations & Supply-Chain optimizations
Dynamic Pricing & Purchase optimization

Catering, Restaurant & Hospitality managers

Automated Forecast tool for Catering, Restaurants & Hospitality management

Industrial Product & Distribution

Dynamic Pricing for B2B
Demand / Supply forecasts
Inventory & Industrial Optimization

Airports & public transports

Affluence and demand forecast
Workforce optimization
Transport / Freight Market Pricing

Financial services

Know your customer, Fraud detection
Anticipate Market evolutions
Dynamic Pricing for B2B Financial Services


Telecom, freight, logistics and more...

Predictions and forecasting the key performance variable of a business is critical to its competitiveness.

Gartner expects that 70% of the most profitable companies will manage business processes using real-time predictive analytics or extreme collaboration.

Predictions and forecasting the key performance variable of a business is critical to it competitiveness of businesses. Gartner expects, 70% of the most profitable companies will manage business processes using real-time predictive analytics or extreme collaboration

Forecasting & Predictive analytics can give a unique competitive advantage in all the function of an enterprise organisation:

  1. To adjust production means to the demand
  2. To minimize inventory without missing any customer opportunity
  3. To optimize logistics & distribution
  4. To target individualized offers for new revenue & profits
  5. To optimize sales and marketing efforts across opportunities
  6. To identify faster and precisely new upsell/crosssell opportunities
  7. To more efficiently drive improvements in customer satisfaction and loyalty
  • Beyond companies' global predictions, how to automate the localisation of these predictions and help every region access their benefits?
  • With artificial intelligence, we can help every local branch benefit from global corporate learning

Predictive Layer has automated the best algorithms to serve the different functions of key sectors where the prediction has a large contribution to the overall revenue and profit of the business.

Predictive Layer's performance allows both savings in costs and / or incremental profitable revenue impacting up to 35% of the bottom line of its users.

Below are selected examples of sectors and use cases where Predictive Layer has improved performance.

Energy Transition is bringing massive disruption into Energy & Utility sectors.
Predictive Analytics has become a unique competitive differentiator to improve operational energy trading & purchase and customer engagement.


Energy Transition, Deregulation and Technologies are massively disrupting Energy and Utility sectors:

  1. Energy transition brings new volatile and versatile renewable sources of energy, and also new mobile and versatile sources of consumption
  2. Open markets and regulations have multiplied and segmented the value chain into multiple players
  3. Industries, smart cities or residential consumers of energy develop more and more control and efficiency in their energy usage

All these elements require the grid to become much smarter and more flexible to be able to cope with versatile demand, at the most affordable price.

To optimize this flexibility and to take the benefits of the data collected by the Internet of things, Smartgrids have to enable automated predictive analytics.

Automated Forecasts allow companies to anticipate and pilot the energy network in real-time with the highest possible efficiency.

They also enable preventive maintenance for an even more reliable utility service delivery.

In addition, added value services need to be deployed to allow customers to monitor, control, adjust and optimize their own consumption (eg. demand/response and load shifting).

Each customer profile also has its own needs and specificities. Energy companies need to understand these customer specificities to profile them and target specific new service offerings to each of them. This leads to increased customer satisfaction & loyalty while limiting the churn of customers to competition.

The Predictive Layer platform has automated predictive analytics. It generates these forecasts, predictions and profiling services automatically and daily.

New energies (ENR)


Source: The Economist 2010

Electricity consumption

Energy Infrastructure includes fast growing renewable energy productions which incorporates highly volatile resources (solar, wind).

Producers can plan energy production and storage of energies with Hydroelectricity, or Batteries. Predictive analytics is key to optimizing the value that they can extract from such energy pools in the markets.

Energy transport and distribution networks are huge investments, with a long life cycle. The new volatility of consumption and production is impacting the balance and aging of these infrastructures.
Furthermore, special environment and external conditions (weather) further impact these systems.

Predictive Layer's automated consumption and production forecasts and its machine learning tool enable our customers to:

  1. Guarantee the technical balance of infrastructure (and reduce Imbalance adjustment costs)
  2. Enable selective predictive maintenance
  3. Build reliable service level agreements with customers & suppliers

Example: Predictive Layer's accurate forecast of next day consumption can save 40+M€ of electricity purchase annually on EU national electricity markets.

To know more about Predictive Layer Automated Predictive Analytics

Energy Management and Optimization for Commercial & Industrial Sectors


As Commercial & Industrial Sectors deploy smart capabilities to measure and control their consumption of energy, with more and more local renewable production, with some local storage capabilities or local flexibilities in consumption, it has become increasingly important to provide the right tools to monitor, track, forecast & optimize the future consumption as well as the new behaviours and perimeter as these commercial sites evolve.

With Predictive Layer's forecasting platform, commercial & industrial energy managers can:

  • Facilitate their daily operations
  • Detect anomalies and accelerate configuration corrections
  • Compare & benchmark sites to recommend evolution or best practice sharing
  • Detect & alert on change of behaviour and new usage patterns
  • Detect key equipment deviation from standard usage patterns to initiate predictive maintenance

The predictive & prescriptive platform can apply
to all utilities with instruments using Sensors & IOT infrastructure:

Utility Control & Optimization
Utility Control & Optimization

Predictive Layer's partnership with Schneider Electric is embedding Predictive Layer's automated forecasting services into Schneider Electric EcoStruxure for Power exchange Platform.

So that all Schneider Electric customers worldwide can access these services in the context of the Schneider Electric solution and ecosystem partners that they have been working with since decades.

For more information, please contact us.

Retailer & Supply Chain Business Challenges

Retail & Supply chain
To remain competitive and differentiate thru digital transformation, retailers need to reach Lean Operations.
During the past years, retailers have consolidated their Big-Data and set-up Business Intelligence.

To reach the next level, Retailers now have to anticipate their key business indicators and use Predictive and Prescriptive Analytics to optimize their workforce efficiency, reduce their inventories while responding with accuracy to their customer's expectations.

Gartner stated: "By 2016, 70% of the most profitable companies will manage business processes using real-time predictive analytics or extreme collaboration".

The Predictive Layer Solution
  • Automated forecasting of business indicators and KPIs
  • Weekly & Intraday, per product category, in each retail point
  • Dynamically taking seasonality into consideration automatically and external influencing factors in each context

Predictive Layer Technologies
  • Machine Learning and Artificial Intelligence for time series
  • Big-Data and Open-Data automatic correlation
  • Prescriptive Operational Metric Forecasts
  • Automated Contextualization & Deployment in 10000+ point

Retailer & Logistic Business Benefits
  • Accurate Weekly/Daily/Intraday Demand Planning
  • Optimize short term Inventory & Logistic management
  • Optimized Planning & Efficiency of Workforces
  • Optimal Shelf Replenishment, before Missed Opportunity
  • Minimize Wasted Inventory on Perishable Products
  • Compare Retails Location for Best Practice Sharing
  • Tune Marketing Activities to reach Business Objectives
Retail & Supply chain

Solution Benefits
  • Extracting business value from historical data
  • Correlating with influential Open-Data: weather, calendar, community events, in-house or competing marketing actions
  • Automated Machine Learning Forecasting with detailed granularity by product category, at each retail point-of-sale, during various seasonal periods or marketing campaigns
  • Automation of model contextualization for scalable deployments into 10000+ retail points-of-sale
  • IT flexibility for in house Data-Center or Secured Hybrid Cloud deployment, with APIs to existing & standard Business Intelligence applications
  • Fast Proof of Concept & Pilot to validate immediate ROI

Retail & Supply chain predictive Layer solution benefits

Catering, Restaurant & Hospitality managers

Retail & Supply chain
Business challenges

In an increasingly competitive market where margin pressure is intense, Caterers, Restaurants, Hospitality managers need to optimize their front-end operations by deploying optimal workforces, with the right skills, to prepare and serve the right number of products at the right time, while minimize waste and avoiding waiting-lines and low-quality deliveries.

Predictive and prescriptive real time analysis has become essential to anticipate daily market demand and prepare the right product to be delivered at the right time & place. Corporate restaurants, Transport catering, Hospitality management require such optimization to deliver a high quality customer experience, while not wasting resources and materials despite volatile demand.

Predictive Layer Solution
  • Automated forecasting of the number of customers, arrival times, their specific requests based on high variety evolving menus
  • Automated correlation of historical records with external variable of influence: weather, calendar, competition. Avoiding waiting-lines by correlating business KPIs with Wifi signal indicators (eg. cooperation with Cisco Systems)
  • Weekly, daily, monthly planning to define and allocate workforces, prepare the right products, supply the exact amount of goods to respond to demand

Predictive Layer Technologies
  • Automated machine learning for time series
  • Self-learning artificial intelligence
  • Big Data and Open-Data and networking data correlation
  • Prescriptive analytics of business KPIs
  • Automated contextualization to any Point-Of-Sales
  • Prediction as a Service

Catering, Restaurant & Hospitality managers Benefits
  • Daily/weekly/monthly optimal planning
  • Increase customer experience quality (avoiding waiting lines)
  • Optimize workforce by 10-20%
  • Reduce waste in preparation (1-3%)
  • Reduce cost of Purchase (2%)
  • Optimize marketing calendars & events
Retail & Supply chain

Industrial Product & Distribution - Dynamic Pricing & Process Optimization

Industrial Product & Distribution
Business challenges

Industrial Products & Distribution companies are facing increasing global competition and margin pressure on commoditizing product lines. Market price and raw material have seasonal and structural volatilities. The product value in the customer value chain varies across industry sectors and local geographic contexts.

Product and services competition, channels and distributors have local specificities and require companies to adapt their global sales and support practices to local needs.

Companies' internal organization has to adjust processes to local contexts, pricing, inventory & support to fit multi-dimensional customer and market specificities.

Predictive Layer Solution
  • Automated demand forecast for products & services for each geography & context
  • Dynamic Pricing adapting to customer's classification, specific markets, quality & support experience, raw material price evolution from industrial company data (ERP CRM BI) and correlating with competitive and external market sources of information
  • Industrial process efficiency optimization
  • Optimize power & raw materials for maximum productivity
  • Supply chain & logistics optimization to reach all regions & branch locations
  • Local and central inventory reduction, purchase optimization
Predictive Layer Technologies
  • Automated machine learning for time series
  • Self-learning artificial intelligence
  • Big-Data and industry market Open-Data correlation
  • Prescriptive Analytics of business KPIs
  • Automated contextualization to any Point-Of-Distribution,
  • Incident Forecast and Predictive Maintenance
  • Prediction as a Service
  • Cooperation with leading infrastructure players for Industry 4.0: GE, Cisco, Schneider Electric

Industrial Product & Distribution Company Benefits
  • Automated forecasts & process optimization
  • B2B Dynamic Pricing to enable up to +4% gross margin improvement
  • +2% market share, 20% sales process efficiency
  • Supply Chain Optimization to reduce inventories by 15%, with no more missed opportunities
  • Supplier purchase optimization by >2%
Industry 4.0

Industry 4.0 companies

Airports & Public Transportation Business Challenges

Airports & Public transports
To benefit from the mobility revolution, airports, railways and public transportation infrastructures need to always increase security, efficiency, comfort and competitivity, by leveraging the digital transformation.
During the past several years, with the advent of IoT & improved telecoms, mass transportation providers and transport infrastructures have collected massive amounts of data on their sophisticated ecosystems and businesses.

To reach the next level, public transport providers have to anticipate their key operational indicators. They must use Predictive and Prescriptive Analytics to optimize their workforce efficiency, improve the customer experience while guaranteeing security within their highly mobile customer base and ever more diverse ecosystem.

Gartner stated: "By 2016, 70% of the most profitable companies will manage business processes using real-time predictive analytics or extreme collaboration".

Predictive Layer Solution
  • Automated forecasting of passenger affluence, next day/week
  • Automated adjustment to evolving context at each gate & hall and in each retail point
  • Adapting automatically to seasonality and external influencing factors from other locations

Predictive Layer Technologies
  • Machine Learning and Artificial Intelligence for time series
  • Big-Data and Open-Data automatic correlation
  • Prescriptive Operational Metric Forecasts
  • Automated Contextualization in thousands of transport hubs
Airports & Public Transportation Business Benefits
  • Accurate daily/intraday passengers @ arrival/departure
  • Forecast Transport Hubs & SmartCities & Parking footfall
  • Resource planning for Security, Logistics, Customs, Retail
  • Workforce Optimization, while controlling Wait-Time/Security
  • Market Retail & Catering opportunities at the most valuable time periods & locations
  • Optimize shared infrastructure allocation (Gates, Tracks...)
  • Increase Passenger & Travel Ecosystem satisfaction
Airports & Public transports

Airports & Public transports
Solution Benefits
  • Extracting business value from historical data
  • Correlating with influential Open-Data: weather, calendar, EuroCtrl flight schedules, real-time traffic, smart-cities traffic & events
  • Automated Machine Learning Forecasting with detailed granularity at each transport hub, hall, during various seasonal periods
  • Automated model contextualization for scalable deployments into thousands of locations
  • IT flexibility: in-house Data-Center or in Secured Hybrid Clouds, SaaS with APIs to existing & standard Business Intelligence applications to preserve business confidentiality & personal data
  • Fast Proof of Concept & Pilot to validate immediate ROI

Retail & Supply chain predictive Layer solution benefits

Financial Services & asset management

Financial services
Financial Products & Services have developed in a massive and global way during past 20 years.

More financial products & services are available daily and/or derived from other products.
Moreover, every day industries and agencies are issuing more open data on markets, supply, demand, transformation, transport.
The Predictive Layer platform automatically correlate the different influences of these variables to predict the future evolutions of these markets for investment, hedging or sales purposes.

Predictive Layer Dynamic Pricing Engine

Genius Pricing can automatically adapt your financial services sales prices to the real time market, the local or market specific supply and to the specificities of your B2B customers.

Artificial Intelligence Machine learning will adapt to market evolution and provide a competitive hedge enabling 5-10% incremental margin, increased market share and better customer satisfaction; while allowing your sales & specialist workforces greater efficiency to focus on customer relationships and high quality service delivery.

Financial services

Financial & Insurance transaction process
By learning automatically from the historical transactions and executed processes to serve customers,

The machine learning platform can automatically anticipate:

  • Potential fraud on transactions
  • Potential impact of process evolution on customer delivery costs & speed
Customer Relationship Management

As financial services and insurance companies develop their customer relationships.

New services and new products could be of great value to the customers during their life time.
The Predictive Layer platform can automatically profile customers, predict the evolution of their requirements over time, so that specific target offerings can be made to each segment.

  • Increases revenue by upsell and crossell, while reducing marketing and sales costs to target the right future customers
  • Increases the customer satisfaction by delivering a focused dedicated services (while avoiding over-communication)
Financial services

Telecom operators and service providers are serving multiple customers segments with ever more complete bundles of services.


It includes mobile communications, but also multimedia and entertainment services and more and more internet applications.
The same users are also simultaneously customers under different contexts: with their enterprise, as personal or family member, as a traveller.
Moreover, the telecom market is also maturing and consolidating in every regions with a fast growing competition.

Telecom operator have been in a unique position to collect many big data on each of their customers.

The Predictive Layer Machine Learning platform uses unique instruments to learn automatically from these core big data.
  They identify and predict the future behaviors of the users as well as their main motivation factor for such behaviors.

Without being a mathematics expert, the telecom operator’s marketing & customer service departments can profile, identify and predict upcoming behaviors:

  • Churn intent
  • Interest in new products
  • Required capacity to allow an SLA delivery

By using Predictive Layer the telecom operator business specialist can take immediate action on prescriptive predictions to target and reach the at-risk customer, motivate them to decrease their churn, propose new services and provision the right capacity to serve them with quality without over investment.

Freight & Logistics has never been more critical for product business


With a market becoming more and more global, being able to produce and ship to all distribution points in due time is key to not miss any customer opportunity.
Meanwhile, warehouse inventories and transport time are major costs and sources of depreciation if not efficiently managed.
Even more so if the products are perishable. It has become essential to permanently balance between demand, supply and logistics timing & costs.
With global demand, the seasonality and the cyclicality of market demand is exacerbated and is very complex to predict and plan.
 Nonetheless, it is now possible to anticipate major seasonal events, calendar of activities in each region, weather, both local, regional and national.

Demand / Supply forecasting

Forecasting short term demand in each region is key to be able to plan supply efficiently, minimize inventories while leveraging the most affordable but reliable freight means.
The Predictive Layer platform will process the available product big data and exogenous data to assess and forecast the short term evolution of product demand.
Even in a context of a wide product portfolio, by using industry open data, but learning from historical records, Predictive Layer allows product managers, logistics team and management to automate accurate predictions of the different volume and value of products in all their regions.

Freight & Transport Optimization

All market players compete for the same resources of transport & freight.
With the exacerbation of seasonality, during high demand periods, transportation capacity is often missing.
Better planning of market demand and supply allow a better control, but competitive industry sectors are often unpredictable for another industry.

Predictive Layer Genius platform is able to access and process the market data of different industries, the transport resource capacities and availabilities, in order to build short term forecasts of the transport & freight activities.
The Predictive Layer platform allows product and distribution companies to forecast and eventually hedge their transportation activities.



Your business could also be under greater control and experience increased value creation if you had the capability to correlate and directly predict some of your key business indicators using your Big Data and/or public / Open data new sources.

  • Without requiring significant mathematics expertise, while accessing the most innovative machine learning algorithms
  • With the option to deploy in a cloud-based service and/or in your own data center or private cloud
  • Predictive Layer has a predictive analytics solution for you
Please let us know about the business problem that you would like to predict...
And we can put a model in place for your optimized usage.

Contact us for use case requirement

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