Business Transformation, Automation and Data Analytics Consultants
Industry Examples
Food Stores that want to scale.
Many food retailers lack the resources to build an organizational structure that can scale.
Successful food retailers who want to scale up their operations require infrastructure. In particular, they require a comprehensive data infrastructure in order to keep track of food quality, food supply and delivery, procurement and various other aspects of the operations. Scaling up a food retail operation implies increasing production without sacrificing quality. The only way to do this is to keep
Fertilizer Manufacturer
Agriculture input producers need to purchase many commodity inputs to produce their products. Purchasing commodity inputs at the right time, right prices and right quantities, can substantially improve the company's profitability in the long run.
We propose to incorporate the use of multiple data sources, both hard and soft data, to develop automated systems that predict the best timing for purchasing inputs.
Many firms lack the resources or expertise to develop such systems in-house. Ideally, firms need to be able to keep track of, analyze and store a lot of data. They also need to be able to quickly understand rapidly changing market environments.
Consumer
Consumer companies today have to grapple with collecting and processing a significant amount of data at multiple levels:
Consumer facing data: consumer preferences, buying habits, reviews among many others
Operations data: inventory management, shipping data, procurement
We work with consumer companies to improve their consumer insights from consumer-facing data, which is useful in marketing and pricing strategy. We also help clients to use the operations data to improve their operational efficiency, minimize inventory problems and improve their procurement strategy.
Most smaller and medium-sized consumer companies lack the resources and expertise to collect, update and process the large amount of data required to run a data-centric business.
Data Analytics for Fundamental Investment Research, Factor Investing, Systematic Investing
The field of Fundamental Investment Research has changed substantially in the past few years with the increasing power of software tools that can substantially increase the productivity of investment research analysts.
Increasing use of Alternative Data
Increasing use of Computer Algorithms to analyze large amounts of data
Increasing use of Web-scraping to collect publicly-available data
Increasing use of Computer Algorithms to develop and test new investment strategies
We work with clients to develop the tools for incorporating data analytics into the field of Fundamental Investment Research.
Most fundamental investment research analysts are not trained as computer programmers.
The time cost of using research analysts to develop computer programs is too high.
Many firms do not have the resources or desire to hire a large team of computer programmers to develop capabilities in-house.
