A2Go begins with an analytic horizon analysis—making better use of data and the best analytics tools available to help them understand the recurring decisions that people make in a way that is most likely to influence outcomes. The solution provider collaborates with their clients to develop proofs of concept followed by a pilot. Through the proof of concept, users can look at historical data to see to understand how they got the results they did and the decisions they made and then learn how they could have improved the outcome with analytically optimized decision making.
“The value of our product is that you can leverage BI, without hiring expensive data scientists, to increase speed and reduce complexities in analytics infrastructure and operations,” states Mike Romeri, CEO at A2Go. The company has an extremely effective and efficient IT platform that they operate on the Microsoft Azure cloud. In doing so, they are able to process massive data sets in parallel, much quicker than a typical company implementing on-premise software applications for their business.
For example, when it comes to consumer sales forecasting without the ability to predict demand accurately under different planning scenarios, any company will have a difficult time optimizing the pricing, marketing, and promotion decisions they make. In A2Go’s experience, the opportunity available from optimizing these decisions can provide up to a 20 percent improvement in incremental revenue and up to a 40 percent improvement in incremental profitability. However, the challenge exists in relying on aggregate demand forecasts for the network, initially based on the previous year’s store sales.
This makes it very difficult to understand the impact of weather, other events, or competitive actions on past results, which are relevant to conducting the strategy for the current year. Using a machine-learning (ML) based approach improves the value of historical information. In a nutshell, the ML solution understands the correlations of historical revenue to the various demand-driving factors very precisely. With ML, the predictive value of using past years’ sales data to guide forecasting is significantly enhanced.This accelerates the process of identifying, understanding, and resolving problems in the market— making the organization more agile. In addition, managerial effectiveness and productivity improve simultaneously due to the automation applied to support their situation analysis. A2Go has significant expertise in helping companies enhance their ability to predict demand and optimize pricing and promotion efforts.
The value of our product is that you can use analytics, without hiring expensive data scientists, to increase speed and reduce the complexity in analytics, infrastructure, and operations
Today, A2Go offers custom solutions. In future, A2Go plans to offer standard applications to an ever-expanding BI market. Their approach will continue to evolve and benefit from significant business domain knowledge in operations, working capital, sales, and marketing. The company has an end-to-end customer lifecycle, and their analytical horizon model adjusts across different industries. With A2Go’s current analytics factory in Brazil and a good supply of data science capability, they want to open up subsequent factories for other places and customers, with a keen eye to building the next in Virginia for a federal customer in the immediate future.