Pre-configured performance templates tailored to your business

Our template library covers the most relevant industry use cases and allows fast & effective deployment.
Why is it so hard to leverage machine learning for your business?

Complexity of adressing business-specifics is often underestimated while technological requirements are overestimated

Lack of understanding in business units on how to utilize Advanced Analytics and Machine Learning

Access to experts with the right set of competencies across different domains

Availability of data at sufficient quality and quantity

Pre-configured Analytics & Machine Learning systems​

Complexity of adressing business-specifics is often underestimated while technological requirements are overestimated
Lack of understanding in business units on how to utilize Advanced Analytics and Machine Learning
Access to experts with the right set of competencies across different domains
Availability of data at sufficient quality and quantity

Performance template repository

Analytics & Machine Learning have already transformed many industries and helped to increase profitability and growth of companies.

Our performance templates leverage Machine Learning for solving domain specific industrial problems. The goal of each template is to enable business owners to leverage data science for their operations and quickly deploy Machine Learning solutions that add value to their business.

Each performance template includes the following:
- A data schema (based on sample dataset) applicable to the specific domain
- Domain specific data processing and feature engineering steps
- Models training algorithms suited to the specific domain
- Domain specific evaluation metrics (if applicable)
- Pre-defined automation flows that trigger actions based on observed data patterns
- Deployment of models and automation flows as a web service

Click on an industry to jump to its solutions

 

Banking and Investments

Including: commercial banking, consumer finance, asset management, investment banking, trading, exchanges, private equity, venture capital, etc.

SolutionImpactDescription
Credit risk assessmentDecrease of provisions for liabilities and charges through more precise risk assessmentBanks can predict the Probability of Default (PD) and Exposure at Default (EAD) more precisely by using Machine Learning models compared to traditional score cards. By modern techniques, explainability of such models is also possible to ensure auditability by regulators.
Call center routingCost reduction for call center operationsBanks can automatically route customers to the best service personnel available massively reducing costs in the call center and time by customer spent on service calls.
Process OptimizationCost reduction through faster business processesBanks can identify potential issues in their business processes through process mining. Using these insights, business processes can be optimized to save costs.
ChurnRevenue increase through extended customer relationshipsBanks can identify likely churners and identify offers that will convince them to stay.
Customer segmentationRevenue increase through improved customer relationshipsBanks can improve their customer understanding in order to adjust tactical and strategic decisions towards their customers' needs.
Branch segmentationRevenue increase through improved store locationsBanks gain transparency on their branches and different types of branches and which services customers use to derive a specific strategy for each location.
Personalized promotionsRevenues through upselling due to more relevant promotionsBanks can make offers to customers based on their needs. By understanding which promotions are meaningful for a specific customer, retailers can move away from mass communication to personalized interactions with their customers.
Branch footprintRevenue increase through improved store footprintBanks can find the ideal location for their next branch or decide which branches to close or merge.
AMLCost reduction through improved AML processesBanks can automatically identify cases of money laundering (shell companies, money mules, etc.) from their transaction data. These insights can be used to optimize the AML process and reduce manual investigations into potential cases of money laundering.

Consumer goods

Including: consumer packaged goods, including food, beverages, make-up, household products.

SolutionImpactDescription
Predictive MaintenanceReduce costs from outagesCPGs can avoid long outage periods of expensive machinery by predicting failures and adjusting maintenance cycles accordingly.
Anomaly detectionReduce costs from production failuresCPGs can avoid production failures through monitoring the production process through sensor data. Anomalies will give an indication of potential problems in the production process.
CustomizationIncrease revenue by better matching customers' preferencesCPGs can customize the production process to specific products by analyzing process data and leveraging efficiencies.
Demand forecastingReduction of inventory costsCPGs can adjust production volume for each product to the actual demand by forecasting it and then adjusting the production planning accordingly.
Purchase order automationIncrease of revenue through a simplified ordering processCPGs can predict demand for supply and automate the ordering process to ensure a seamless production with just-in-time deliveries.
Quality assuranceReduce costs from production failuresCPGs can identify reasons for production failures by analyzing sensor data from the involved machines. They can identify which states of the machines were responsible for the production failures in order to take actions and avoid the errors.
Planning and schedulingCost reduction through better production planningCPGs can optimize their production planning by merging demand, supply and process information and establish a schedule that has short downtimes and highest output.
Energy efficiencyCost reduction of energy expensesCPGs can reduce energy usage by identifying process steps with high energy usage and adjusting the whole process to minimize energy costs (or to maximize overall profitability).
Shift planningCost reduction through better shift planningCPGs can optimize the schedule for shift workers based on availability, required skill levels, production planning etc.
Product optimizationIncrease of revenue through improved productsCPGs can adjust their products by gaining a better understanding of links between the production process, suppliers, product quality, and customer demand.
Supply chain optimizationCost reduction through reduced product complexity and improved supply chainCPGs can optimize supply, delivery routes, intermediate storage etc., to reduce logistics costs.
Stock optimizationCost reduction from reduced stockCPGs can minimize stock keeping for a given service level for their customers.
PricingMargin increase through optimized pricingCPGs agencies can optimize their pricing strategy by identifying willingness to pay by retailers. Also, CPGs can use competitive intelligence to adjust their prices in order to have a better position in negotiations with retailers.

Consumer durable goods and apparel

Including: cars and accessories, electronics, furniture, apparel, clothing, appliances, etc.

SolutionImpactDescription
Demand forecastingReduction of inventory costsCPGs can adjust production volume for each product to the actual demand by forecasting it and then adjusting the production planning accordingly.
Purchase order automationIncrease of revenue through simplified ordering processCPGs can predict demand for supply and automate the ordering process to ensure a seamless production with just-in-time deliveries. This will also reduce the costs of stock-keeping.
Quality assuranceReduction of costs from production failuresCPGs can identify reasons for production failures by analyzing sensor data from the involved machines. They can identify which states of the machines were responsible for the production failures in order to take actions to avoid the errors.
Predictive MaintenanceReduce costs from outagesCPGs can avoid long outage periods of expensive machinery by predicting failures and adjusting maintenance cycles accordingly.
Anomaly detectionReduction of costs from production failuresCPGs can avoid production failures through monitoring the production process through sensor data. Anomalies will give an indication of potential problems in the production process.
CustomizationIncrease revenue by better matching customers' preferencesCPGs can customize the production process to specific products by analyzing process data and leveraging efficiencies.
Planning and schedulingCost reduction through better production planningCPGs can optimize their production planning by merging demand, supply and process information and establish a schedule that has short downtimes and highest output.
Energy efficiencyCost reduction of energy expensesCPGs can reduce energy usage by identifying process steps with high energy usage and adjusting the whole process to minimize energy costs (or to maximize overall profitability).
Shift planningCost reduction through better shift planningCPGs can optimize the schedule for shift workers based on availability, required skill levels, production planning etc.
Product optimizationIncrease of revenue through improved productsCPGs can adjust their products by gaining a better understanding of links between the production process, suppliers, product quality, and customer demand.
Supply chain optimizationCost reduction through reduced product complexity and improved supply chainCPGs can optimize supply, delivery routes, intermediate storage etc. to reduce logistics costs.
Stock optimizationCost reduction from reduced stockCPGs can minimize stock keeping for a given service level for their customers.
PricingMargin increase through optimized pricingCPGs agencies can optimize their pricing strategy by identifying willingness to pay by retailers. Also, CPGs can use competitive intelligence to adjust their prices in order to have a better position in negotiations with retailers.

E-Commerce

Including: B2C including online retail clothing, drugs, special interest, etc.; B2B including business processes, cloud services, marketplaces.

SolutionImpactDescription
Promotion effectivenessCost reduction for promotionsE-commerce players gain transparency on the effectiveness of promotion activities (revenue, margin, website visits) to develop strategies for more impact-focused campaign management and discounts.
Customer segmentationRevenue increase through improved customer relationshipsE-commerce players gain transparency on their customers and different customer groups. They can make campaigns and offers more targeted and streamline the assortment towards customer needs.
Dynamic pricingMargin increase through optimized pricingE-commerce players can optimize their pricing strategy by identifying key value items, i.e. products for which price is exceptionally important. In addition, retailers can use competitive intelligence through web crawling to adjust their prices dynamically.
Personalized promotionsRevenue increase through upsellingE-commerce players can make customer offers to customers based on their needs. By understanding which promotions are meaningful for a specific customer, retailers can move away from mass communication to personalized interactions with their customers.
Assortment optimizationCost reduction through reduced product complexity and improved supply chain.E-commerce players can tailor their assortment towards customer needs de-listing products that are substitutable and reduce complexity of the entire supply chain.
Demand forecastingCost reduction for stocks and revenue increase through additional salesE-commerce players gain insights on customer demand for every product in advance and can plan logistics and sales accordingly
Stock optimizationReduction of inventory costsE-commerce players minimize stock keeping at a given service level for their customers.
Vendor negotiationsMargin improvement through better purchase pricesThrough a better understanding of products and assortment e-commerce players have an advantage over their suppliers in vendor negotiations.
Supply Chain OptimizationCost reduction in the supply chainE-commerce players can optimize delivery routes, intermediate storage etc., to reduce logistics costs.
Branch footprintRevenue increase through improved store locationsE-commerce players can find the ideal location for their next branch or decide which stores to close or merge.
Trend forecastingIncrease revenues through increased sales volumeE-commerce players can predict future customer trends to plan purchases and sales strategies ahead.
Fraud detectionReduce costs through reduced fraudE-commerce players can detect fraudulent activity from users and reduce susceptibility to fraud.

Agriculture and farming

SolutionImpactDescription
Yield optimizationIncrease of revenue through additional yieldAgriculture companies can identify drivers for high yield in very complex production or farming processes. They can find the optimal set of control levers for reaching the highest output of the production process.
Planning and schedulingCost reduction through better production planningAgriculture companies can optimize their production planning by merging demand, supply and process information and establish a schedule that has short downtimes and high output.
Energy efficiencyCost reduction of energy expensesAgriculture companies can reduce energy usage by identifying process steps with high energy usage and adjusting the whole process to minimize energy costs (or to maximize overall profitability).
Predictive MaintenanceReduce costs from outagesAgriculture companies can avoid long outage periods of expensive machinery by predicting failures and adjusting maintenance cycles accordingly.
Anomaly detectionReduce costs from production failuresAgriculture companies can avoid production failures through monitoring the production process through sensor data. Anomalies will give an indication of potential problems in the production process.
Demand forecastingReduction of inventory costsAgriculture companies can adjust production volume for their product to the actual demand by forecasting it and then adjusting the production planning accordingly.
Purchase order automationIncrease of revenue through simplified ordering processAgriculture companies can predict demand for supply and automate the ordering process to ensure a seamless production with just-in-time deliveries. This will also reduce costs of stock keeping.
Quality assuranceReduction of costs from production failuresAgriculture companies can identify reasons for production failures by analyzing sensor data from the involved machines. They can identify which states of the machines were responsible for the production failures in order to take actions and avoid the errors.
Shift planningCost reduction through better shift planningAgriculture companies can optimize the schedule for shift workers based on Agriculture companies, required skill levels, production planning etc.
Supply chain optimizationCost reduction through reduced product complexity and improved supply chainAgriculture companies can optimize supply, delivery routes, intermediate storage etc. to reduce logistics costs
Stock optimizationCost reduction from reduced stockAgriculture companies can minimize stock keeping for seeds, fertilizer and harvest
Crop diseases and pestsMinimize costs through crop diseases and pestsAgricultural pests can quickly cut into a farmer's profits. But, misusing pesticides can have adverse effects on people, plants and other living things. But agriculture companies can develop user-facing platforms that analyze when to apply pesticides and how much to use.
Yield predictionReduced costs through better planningSatellite-based crop monitoring to inspect areas can help agriculture companies to get prompt updates and alerts about potential problems.

Industrials

Including: buildings, electronics, aerospace, machinery, etc.

SolutionImpactDescription
Shift planningCost reduction through better shift planningIndustrials can optimize the schedule for shift workers based on availability, required skill levels, production planning etc.
Product optimizationIncrease of revenue through improved productsIndustrials can adjust their products by gaining a better understanding of links between the production process, suppliers, product quality, and customer demand.
Supply chain optimizationCost reduction through reduced product complexity and improved supply chainIndustrials can optimize supply, delivery routes, intermediate storage etc. to reduce logistics costs.
Predictive MaintenanceReduce costs from outagesIndustrials can avoid long outage periods of expensive machinery by predicting failures and adjusting maintenance cycles accordingly.
Anomaly detectionReduce costs from production failuresIndustrials can avoid production failures through monitoring the production process through sensor data. Anomalies will give an indication of potential problems in the production process.
CustomizationIncrease revenue by better matching customers' preferencesIndustrials can customize the production process to specific products by analyzing process data and leveraging efficiencies
Demand forecastingReduction of inventory costsIndustrials can adjust production volume for each product to the actual demand by forecasting it and then adjusting the production planning accordingly.
Purchase order automationIncrease of revenue through simplified ordering processIndustrials can predict demand for supply and automate the ordering process to ensure a seamless production with just-in-time deliveries. This will also reduce costs of stock keeping.
Quality assuranceReduction of costs from production failuresIndustrials can identify reasons for production failures by analyzing sensor data from the involved machines. They can identify which states of the machines were responsible for the production failures in order to take actions and avoid the errors.
Planning and schedulingCost reduction through better production planningIndustrials can optimize their production planning by merging demand, supply and process information and establish a schedule that has short downtimes and highest output.
Energy efficiencyCost reduction of energy expensesIndustrials can reduce energy usage by identifying process steps with high energy usage and adjusting the whole process to minimize energy costs (or to maximize overall profitability).
Stock optimizationCost reduction from reduced stockIndustrials can minimize stock keeping for a given service level for their customers

Materials production & processing

Including: chemicals, construction, packaging, metals, paper, etc.

SolutionImpactDescription
Call center routingCost reduction for call center operationsUtilities can automatically route customers to the best service personnel available significantly reducing costs in the call center and time by customer spent on service calls.
Predictive Issue identificationCost reduction through faster identification of failuresUtilities can identify potential issues in their power plants and grid in order to avoid long troubleshooting processes with service personnel.
ChurnRevenue increase through extended customer relationshipsUtilities can identify likely churners and identify offers that will convince them to stay.
Predictive MaintenanceCost reduction for through reduced number of outagesUtilities can avoid outage periods of machinery in their power plants predicting failures and adjusting maintenance cycles accordingly.
Customer segmentationRevenue increase through improved customer relationshipsUtilities can improve their customer understanding in order to adjust tactical and strategic decisions towards their customers' needs.
PricingMargin increase through optimized pricingUtilities can optimize their pricing strategy by identifying willingness to pay. Also, utilities can use competitive intelligence to adjust their prices and leverage local and temporal information to make prices dynamic.
Personalized promotionsRevenues through upselling due to more relevant promotionsUtilities can make customer offers to customers based on their needs. By understanding which promotions are meaningful for a specific customer, retailers can move away from mass communication to personalized interactions with their customers.
Lead generationRevenue increase through additional customersUtilities can identify high-value leads to target by leveraging public and buyable information (e.g. demographics, potential customers moving, etc.)
Fraud detectionCost reduction from reduced fraudUtilities can detect and avoid fraud through customers or customers unable to pay their utility bills.

Retail and distributors

Including: stationery, food, clothing, drugs, hypermarkets, special interest, etc.

SolutionImpactDescription
Promotion effectivenessCost reduction for promotionsRetailers gain transparency on the effectiveness of promotion activities (revenue, margin, store visits) in order to develop strategies for more impact-focused campaign management and discounts.
Assortment optimizationCost reduction through reduced product complexity and improved supply chainRetailers can tailor their assortment towards customer needs by de-listing products that are substitutable and therefore reduce complexity in the entire supply chain.
Vendor negotiationsMargin improvement through better purchase pricesThrough a better understanding of products and assortment, retailers have an advantage over CPGs in vendor negotiations.
Customer segmentationRevenue increase through improved customer relationshipsRetailers gain transparency on their customers and various customer groups. They can make campaigns and offers more targeted, and streamline the assortment towards customer's needs.
Store segmentationRevenue increase through improved store footprintRetailers gain transparency on their stores and different types of stores which helps them to derive a specific strategy for each sales location.
PricingMargin increase through optimized pricingRetailers can optimize their pricing strategy by identifying Key Value Indicators, i.e. products for which price is exceptionally important. Also, retailers can use competitive intelligence to adjust their prices and leverage local and temporal information to make prices dynamic.
Personalized promotionsRevenue increase through upsellingRetailers can make customer offers to customers based on their needs. By understanding which promotions are meaningful for a specific customer, retailers can move away from mass communication to personalized interactions with their customers.
Demand forecastingCost reduction for stocks and revenue increase through additional salesRetailers gain knowledge of customer demand for every product in advance and can plan logistics and sales accordingly.
Stock optimizationReduction of inventory costsRetailers minimize stock keeping at a given service level for their customers.
Supply Chain OptimizationCost reduction in the supply chainRetailers can optimize delivery routes, intermediate storage etc. to reduce logistics costs.
Branch footprintRevenue increase through improved store locationsRetailers can find the ideal location for their next branch or decide which stores to close/merge.
Trend forecastingIncrease revenues through increased sales volumeRetailers can predict future customer trends to plan purchases and sales strategies ahead.
Fraud detectionReduce costs through reduced fraud Retailers can detect and avoid fraud through own staff or customers.