Industry domains expertise

Leading organizations leverage Big Data analytics and AI technologies to drive smarter, faster and more accurate decisive actions in every part of their business. Factlabs serves as a strategic partner to them where we consult and deliver a wide range of Big Data Analytics and AI services for centralized analytics teams or individual business units.

Below is a list industries with few indicative use cases for them –

1.Healthcare

  • Claims review prioritization
  • payers picking which claims should be reviewed by manual auditors
  • Medicare/medicaid fraud
  • Tackled at the claims processors, EDS is the biggest & uses proprietary tech
  • Medical resources allocation
  • Hospital operations management
  • Optimize/predict operating theatre & bed occupancy based on initial patient visits
  • Alerting and diagnostics from real-time patient data
  • Embedded devices (productized algos)
  • Exogenous data from devices to create diagnostic reports for doctors
  • Prescription compliance
  • Predicting who won’t comply with their prescriptions
  • Physician attrition
  • Hospitals want to retain Drs who have admitting privileges in multiple hospitals
  • Survival analysis
  • Analyse survival statistics for different patient attributes (age, blood type, gender, etc) and treatments
  • Medication (dosage) effectiveness
  • Analyse effects of admitting different types and dosage of medication for a disease
  • Readmission risk
  • Predict risk of re-admittance based on patient attributes, medical history, diagnose & treatment

2. Consumer Financial

  • Credit card fraud
  • Banks need to prevent, and vendors need to prevent
  • Retail (FMCG – Fast-moving consumer goods)
  • Pricing Optimize per time period, per item, per store
  • Was dominated by Retek, but got purchased by Oracle in 2005. Now Oracle Retail.
  • JDA is also a player (supply chain software)
  • Location of new stores
  • Pioneerd by Tesco
  • Dominated by Buxton
  • Site Selection in the Restaurant Industry is Widely Performed via Pitney Bowes AnySite
  • Product layout in stores
  • This is called “plan-o-gramming”
  • Merchandizing
  • when to start stocking & discontinuing product lines
  • Inventory Management (how many units)
  • In particular, perishable goods
  • Shrinkage analytics
  • Theft analytics/prevention (http://www.internetretailer.com/2004/12/17/retailers-cutting-inventory-shrink-with-spss-predictive-analytic)
  • Warranty Analytics
  • Rates of failure for different components
  • And what are the drivers or parts?
  • What types of customers buying what types of products are likely to actually redeem a warranty?
  • Market Basket Analysis
  • Cannibalization Analysis
  • Next Best Offer Analysis

3. Insurance

  • Claims prediction
  • Might have telemetry data
  • Claims handling (accept/deny/audit), managing repairer network (auto body, doctors)
  • Price sensitivity
  • Investments
  • Agent & branch performance
  • DM, product mix

4.Construction

  • Contractor performance
  • Identifying contractors who are regularly involved in poor performing products
  • Design issue prediction
  • Predicting that a construction project is likely to have issues as early as possible

5.Life Sciences

  • Identifying biomarkers for boxed warnings on marketed products
  • Drug/chemical discovery & analysis
  • Crunching study results
  • Identifying negative responses (monitor social networks for early problems with drugs)
  • Diagnostic test development
  • Hardware devices
  • Software
  • Diagnostic targeting (CRM)
  • Predicting drug demand in different geographies for different products
  • Predicting prescription adherence with different approaches to reminding patients
  • Putative safety signals
  • Social media marketing on competitors, patient perceptions, KOL feedback
  • Image analysis or GCMS analysis in a high throughput manner
  • Analysis of clinical outcomes to adapt clinical trial design
  • COGS optimization
  • Leveraging molecule database with metabolic stability data to elucidate new stable structures

6.Hospitality/Service

  • Inventory management/dynamic pricing
  • Promos/upgrades/offers
  • Table management & reservations
  • Workforce management (also applies to lots of verticals)
  • Electrical grid distribution
  • Keep AC frequency as constant as possible

7. Manufacturing

  • Sensor data to look at failures
  • Quality management
  • Identifying out-of-bounds manufacturing
  • Visual inspection/computer vision
  • Optimal run speeds
  • Demand forecasting/inventory management
  • Warranty/pricing

8.Travel

  • Aircraft scheduling
  • Seat mgmt, gate mgmt
  • Air crew scheduling
  • Dynamic pricing
  • Customer complain resolution (give points in exchange)
  • Call center stuff
  • Maintenance optimization
  • Tourism forecasting

9.Agriculture

  • Yield management (taking sensor data on soil quality – common in newer John Deere et al truck models and determining what seed varieties, seed spacing to use etc

10 .Mall Operators

  • Predicting tenants capacity to pay based on their sales figures, their industry
  • Predicting the best tenant for an open vacancy to maximize over all sales at a mall

11. Education

  • Automated essay scoring

12 . Utilities

  • Optimize Distribution Network Cost Effectiveness (balance Capital 7 Operating Expenditure)
  • Predict Commodity Requirements
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