Our Solutions

Banking and Financial Services

Analytics is helping the banking industry become smarter in managing the myriad challenges it faces. No longer are the times of basic reporting and descriptive analytics. Today’s banks are investing in predicative analytics by improving risk assessment and predicting customer behavior. “Every single major decision to drive revenue, to control costs, or to mitigate risks can be infused with data and analytics,” by improving risk assessment and predicting customer behavior.

We help customers understand consumer behavior, respond to changes in customer’s behaviors, meet regulatory requirements, and improve product portfolio optimizations. We are helping banks achieve profitable growth in an environment with significant volatility across asset classes and rising losses in traditional banking products.


Healthcare industry is continuously generating large amounts of data in different forms, it is almost impossible to manage this data over soft or hard copy formats. The current trend favors digitization of these large amount of data. Driven by mandatory requirements, the current generation favors “Data Analytics”. With an effective data analytics approach, it is easy to plan and manage the decision related to healthcare issues. These data analytics solutions include progressive real-time and predictive techniques that aggregate disparate data across diverse care settings.

“Due to growing competitive pressures, hospitals need to provide comprehensive reporting on performance and quality measures to a variety of stakeholders. Advanced analytics capabilities are absolutely critical for survival – there is no way to avoid it.”

Use Cases:

  • Patient Readmission
  • No Show Predictor
  • Reducing Administrators Costs
  • Clinical Decision Support
  • Cutting Down Fraud and Abuse
  • Data Warehousing for EHR Systems
  • Public Health

Logistics and Transportation

Descriptive, Predictive, and Prescriptive analytics are changing the way logistics and transportation is running their businesses. Many companies are building analytics strategies, which use data to facilitate better decisions. Obtaining a lot of data does not guarantee the ability to better understand what is happening in the supply chain, but using that data to improve how you describe or report on your supply chain makes a world of difference. If a supplier’s shipment misses its scheduled vessel, the BI tool alerts management to take action, such as using air freight if arrival time is important, or waiting for the next ship if inventory is available to meet upcoming orders. Forecasting future demand patterns based on past demand patterns; using internal and external data to estimate rates on various transportation lanes; and consulting customer order patterns to predict which items move together and which move in the opposite direction. Being able to accurately predict outcomes allows you to develop smarter strategies.

While traditional statistical analysis used only the data available within the organization, predictive analytics now merges your data with externally available data to develop better results. Routing trucks to make a set of deliveries is a good example. If you know the deliveries and the cost of the trucks, an optimization engine can find a solution that is 10 to 15 percent better than what you could find manually. The trend toward prescriptive analytics and optimization involves embedding optimization to help make decisions closer to real time. For instance, ocean carriers can use optimization to determine how to best return empty containers to demand points. Retailers can supplement their replenishment systems with optimization to better balance inventory levels, promotional pricing, full truck pricing, and service levels.


With marketing being the biggest IT spend, all eyes are on the success of the teams. In today’s digital age marketing is an imperative measure to increase ROI and determining the company’s spend. Evaluating the success of your marketing behavior can give companies a detailed look into what users are doing on web and mobile properties, or how much time they are spending within an application. How and where web users congregate, which buttons get pushed most frequently or usage rates for certain features. The data is also extremely powerful for marketers. By using predictive analytics, you could compare retention rates for users based on the marketing campaign that “brought them in” to see which ones resulted in the most valuable long-term customers. Predictive Analytics helps build the brand, increase the viewers on media, and expand the portfolio.

Use Cases:

  • Budget Planning
  • Monitor and Tracking Results
  • User Rates
  • Campaigning


In every decision today executives are making some kind of forecast. Forecasting models enable us to identify, collect and manage data, and business needs related to predictive analytics to generate improved results. The selection of a method depends on many factors—the context of the forecast, the relevance and availability of historical data, the degree of accuracy desirable, the time period to be forecast, the cost/ benefit (or value) of the forecast to the company, and the time available for making the analysis.

A successful forecast asks the following questions:

  1. What is the purpose of the forecast—how is it to be used?
  2. What are the dynamics and components of the system for which the forecast will be made?
  3. How important is the past in estimating the future?

Supply Chain

Predictive analytics examines raw data to help draw conclusions for your supply chain. Relying on traditional supply chain execution systems is becoming increasingly more difficult, with a mix of global operating systems, pricing pressures and ever increasing customer expectations. There are also recent economic impacts such as rising fuel costs, the global recession, supplier bases that have shrunk or moved off-shore, as well as increased competition from low-cost outsourcers. All of these challenges potentially create waste in your supply chain. Supply chain is a great area for analytic tools to look for a competitive advantage, because of its complexity and also because of the prominent role supply chain plays in a company’s cost structure and profitability.

Human Resources

People are the backbones to the success of your company. As we all know companies don’t run unless our people are happy. HR analytics is now termed “Peoples Analytics.” HR analytics helps the customers solve what they want; information that helps them run the company better: “Get me the right people into the job, make them productive and happy, and get them to help us attract more customers and drive more revenue.

Governance Risk and Compliance

This is one of the hottest topics in the industry. Every company has compliance and regulations they must abide by and are constantly turning to technology to help them make this area much easier. GRC solutions enable you to adapt to change and meet risk and regulatory compliance head on with technology that predicts, adapts, and integrates.

Historically, analytics has been synonymous with business Intelligence — knowing the facts and reporting past and current performance. But today risk analytics is more focused on data exploration, segmentation, statistical clustering, predictive modeling, and event simulation and scenario analysis.

Questions to be asking in GRC:

  1. When should the data be extracted?
  2. How should it be reconciled?
  3. Does it need to be archived, and if so for how long?
  4. How long until it can be deleted?
  5. What audit evidence must be stored?

Internet of Things

IoT is a topic on everyone’s mind today. The data that goes along with this is massive. Our thermostats, lightbulbs, and refrigerators are all collecting data. Not to mention the beacons and sensors that are collecting data in the retail, energy, and manufacturing industries. Predictive analytics is helping to shape the future not just by lifestyle enhancement but corporations are enabling organizations to collect and analyze data from sensors on manufacturing equipment, pipelines, weather stations, smart meters, delivery trucks and other types of machinery. With an eye toward reducing maintenance costs, avoiding equipment failures and improving business operations. The world of IoT is endless on what predictive analytics can help to achieve.

Use Cases:

  • Insurance Rates
  • Wind Turbine
  • Cell Tower
  • Manufacturing plants


Who is lurking in your environment today? We all know by now that the bad guys are getting in. It’s not just a matter of when the attack happened but how is the attack happening. Predictive analytics cuts down the time for the analysts to spot the anomaly. Consolidating data silos, and helping to identify and quickly remediate the threat is on every analyst’s mind. Addressing regulatory mandates and detecting insider fraud helps businesses better predict risks. Predictive analytics for IT security isn’t just a want but a need in today’s world.

Use Cases:

  • Detection of zero-day threats through traffic profiling
  • Compliance with policy and regulatory mandates via deep analysis of application data and protocols
  • Social media monitoring
  • Advanced incident analysis via correlation of flow data with log data
  • Continuous profiling of assets
  • Network topology views and centralized configuration auditing
  • Rule change modelling and threat simulations
  • Policy monitoring and reporting

Manufacturing and Distribution

Manufacturers are taking advantage of advanced analytics to reduce process flaws, saving time and money. Manufacturers have an abundance of operational and shop floor data that is being used for tracking today.


  • Better forecasts of product demand and production
  • understanding plant performance across multiple metrics
  • providing service and support to customer’s faster
  • Greater visibility into supplier quality levels, and greater accuracy in predicting supplier performance over time
  • Measuring compliance and traceability to the machine level becomes possible
  • Selling only the most profitable customized or build-to-order configurations of products that impact production the least
  • Breaking qualitymanagement and compliance systems out of their silos and making them a corporate priority
  • Quantify how daily production impacts financial performance with visibility to the machine level
  • Service becomes strategic and a contributor to customers’ goals by monitoring products and proactively providing preventative maintenance recommendations
  • Increasing the accuracy, quality and yield of biopharmaceutical production.


Retail is ever changing and evolving to stay ahead of the competition. Predictive analytics is making it even easier. With a better understanding of who the customers are, where they are shopping, how they are shopping, gives companies the edge they need to help customers stay in the stores longer, offering guided routes to certain items, special offerings on items they have purchased in the past, coupons to help build sales. Companies are investing in “Customer Analytics.”

Use Cases:

  • Beacons
  • Store Tracker
  • Traffic Patterns
  • Upcoming sales predictions


Customer retention is more important than ever for companies in the Telecommunications Industry. With the main goals to boost loyalty, reduce churn, improve operational efficiency, and support new business models, Telecom companies are turning to Predictive analytics to turn the industry around. Telecom companies need to leverage and integrate massive amounts of data from a range of sources -like Call Data Records (CDR), customer care, product/service portfolios, cost and billing, and network service quality in a holistic way, minimizing the poor alignment between siloed departments.

Use Cases

  • Immediately identify cross-selling opportunities.
  • Prevent customer churn and detect upselling opportunities.
  • Send effective acquisition and retention campaigns that match the right customers with the right products.


The smart grid, smart meters and increasing quantities of intelligent devices have put an unprecedented amount of data into the laps of utility companies. Not to mention the CRM systems used in customer service departments. It’s no wonder they are reaching out to predictive analytics to help guide customer experiences, end incorrect meter readings, alert to faulty equipment or malfunction. We help clients reduce consumption, increase returns, lower risk and enhance reputations. Our solutions reinvent the customer experience to achieve better cost-effectiveness and deeper market penetration.