Inventory Optimization
Issues & Objectives
- One of world’s largest mining corporation having a network of 9 mines
- Approximately $ 400 million working capital used to manage spares inventory of about 182K SKUs
- Stock position monitored by the MRP system every ½ hour & orders are placed
- Objective was to propose improvement to spares inventory management at each storage location to minimize locked up working capital while meeting SLAs
Benefits
- 20% savings in working capital ~ $ 80 million
- The existing MRP database was updated with new ROP & EOQ
Project information
Skills
Operations Research
Client
One of Largest Mining Corporation
Domain
Supply Chain & Retail
Location
Australia
Challenges
- Large number of SKUs ~182K
- Demand variations
Solution
- Derived inventory policy at the network level from ROP and EOQ
- Identified 9 different models for distributions of demand volume
- Developed an ML decision tree for choosing appropriate model based on value & velocity
- Computed EOQ using selected model
What we build, how it performs – Explore our work!
Would love to hear your thoughts!
Smart Analysis on Bus Transportation System
Issues & Objectives
Transport regulatory authority in Singapore commissioned a system to
- Automatically discover wrong fare incidents and flag commuter’s cards affected by wrong fare charging; and
- Detect emerging fault trends in fare collection equipment so that corrective action could be taken in a timely manner
Challenges
- Large data 15 million transactions per day, which translates to more than 5 billion historical transactions in a year needs to be processed to identify fault patterns and trends
- The data consisted of financial, operations, transit and events data of buses
Project information
Skills
Advanced Statistical Model
Client
Transportation Authority
Domain
Big Data Analytics
Location
Singapore
Solution
- Data Storage: Hadoop and MySQL
- Query Tools: Hive and SQL
- Algorithms: rmr (Parallel versions of R) and Java
- Reporting and Dashboards: Pentaho
Results
Robust solution in use for over 2 years allows pro-active rather than reactive maintenance
What we build, how it performs – Explore our work!
Would love to hear your thoughts!
Distribution Analytics – Demand Forecast
Issues & Objectives
- A Singapore based company provide multi country mobile platform for distributed sales representatives who gets updated information on demand forecast, recommendation and target sale
- They wanted to build appropriate models for forecast
- All output were to be pre processed in nightly batch run and saved in a centralized database
- A customized software for managerial decision making was also needed
Benefits
- Batch run for a dataset of 60K transaction take less than 10 minutes producing multiple output tables
- Experiment with customer segments and view a particular subset for any discount/promotion
- View the position of customers and the recommendation to be made
- Review the profile of DSR and extent of target achievement
- Employ Various methods and visualize actual vs forecast
Project information
Skills
Advanced Statistical Model
Client
SaaS Provider
Domain
Demand Forecasting
Location
Singapore
Challenges
- High attrition of DSRs made it hard to collate a time series sales data
- Customer base changes between transition from one DSR to another
- Intermittent sales data for about 30% of customers
- Discontinued or new product SKUs with short history of sales data
Solution
- Software developed in R Shiny
- K-means and hierarchical clustering and time series forecasting methods were used
- Batch code is developed in R with input and output link to client database
What we build, how it performs – Explore our work!
Would love to hear your thoughts!
Airline O&D Passenger & Revenue Forecasting
Issues & Objectives
- Forecast passenger and revenue for major O&D (Origin & Destination)/POS (Point of Sale) combinations for a large East African Airline
- Short term O&D forecasts for every flight date up to 90 days in the future to be generated everyday
- Long term rolling forecasts up to 5-10 years to be generated quarterly
Methodology
- Linear Regression
- ARIMA/ARIMAX
- Neural Networks
- Etc.
Project information
Skills
Advanced Statistical Model
Client
Budget Airlines
Domain
Revenue Management
Location
Africa
Data
Short term forecasts based on:
- Current bookings
- Historical bookings
- Seasonality
- DOW (Day-of-Week)
- Etc.
Long term forecasts based on:
- GDP
- Population growth at origin
- Population growth at destination
- Employment growth at origin
- Employment growth at destination
- Etc.
Solution
- O&D forecasting is very challenging because of the small numbers involved
- Good accuracies obtained
What we build, how it performs – Explore our work!
Would love to hear your thoughts!
Ad-Spot Optimizer (ASO)
Issues & Objectives
- Generate in real time (typically a few minutes) the daily spot allocation plan which determines the program/breaks in which each spot will be aired
Benefits
- Maximizes revenue ( 2-4% incremental gain)
- Automates the spot allocation process
- Respects FCT Caps
- All allocation rules such as cap on number of ads for the same brand in a program are satisfied
- Checks that all deal conditions are satisfied while allocating ads
Project information
Skills
Mathematical Optimization Models
Client
Leading TV Broadcaster
Domain
Media Analytics
Location
India
Solution
Designed and developed a software with following features
- Assured allocation at spot, brand, advertiser, deal level
- Even distribution of spots of different brands, products, clients when the rates are same
- Long term even distribution of spots across day-parts from each deal time-band
What we build, how it performs – Explore our work!
Would love to hear your thoughts!
Ad Revenue Optimiser
Issues & Objectives
- Creating advertising proposals is a vital aspect of a broadcaster’s operations, as it centres around persuading advertisers to commit to investing in advertising slots or campaigns on the broadcaster’s platforms. These proposals encompass different rates for different advertisers based on the frequency and quantum of ad bookings
- Ad Revenue Optimiser (ARO) is a web application to automate and optimise advertisement inventory planning for the client resulting in additional revenue gain. The solution focuses on creation of proposals, planning of ad inventory and post evaluation
Project information
Skills
Mathematical Optimization Models
Client
One of Leading Broadcasters in Asia
Domain
Media Analytics
Location
India
Solution
Designed and developed a software serve clients evolving requirements like
- State of the art inventory visualisation
- Advertising on digital and mobile platforms
- Interactive content
- Comprehensive sales management
Benefits
- Improved inventory pricing
- Improved allocation of inventory
- Improved pipeline visibility
- Sales executives performance tracking
- Negotiations history tracking for future reference
- Improved handling of Make goods
- Streamlined, accurate and faster billing
What we build, how it performs – Explore our work!
Would love to hear your thoughts!