International Institute for Analytics

Inquiry:

Our data and analytics group is six months old, and we’re challenged by many things: creating an intake process, developing the community, managing data ownership. We’re a heavily top-down organization—with the executives dictating our strategic initiatives for analytics—so we wonder if an analytics pipeline would fit into our culture.

United Parcel Service (UPS) is now well known for instituting ORION, an optimized routing system for UPS drivers that has been called the world’s largest operations research project. ORION determines the most efficient delivery route for every driver, every day, resulting in savings of more than 100 million driving miles. The project serves as an excellent case study on how embedding analytics and models within the day-to-day operations of the business—in this case, package delivery—can reap huge cost savings benefits.

Inquiry:

I’m leading the effort to embed analytics teams into other business functions, but I want their allegiance to be to analytics rather than the function they support. How do you create enough autonomy to ensure integration with the business units, while at the same time ensuring the teams don’t go native?

Inquiry:

We’re primarily known as a data company, and we are currently creating new capabilities for our customers, leveraging AI and machine learning. Our mandate is to use AI for competitive advantage going forward. How do we increase our competitive advantage and drive AI transformation in the company?

Traditionally, large organizations have both a research organization and a customer analytics organization that are distinct from each other and often in entirely different chains of command. I have seen many organizations where there is tension between these two organizations. Neither seems willing to acknowledge the value of the other and this causes opportunities to be missed. Today, organizations need to challenge the old assumption that these groups should be separated.

Don’t let your data sit there, get after it. This blog covers 3 examples of projects we’ve worked on that should give you some ideas of what it’s like to explore what you own and what’s possible.

Driving growth at Morgan Stanley is about equipping its 16,000 financial advisors to efficiently deliver personal, customized advice to clients in dynamic markets. Morgan Stanley is making tremendous investments in creating real-time decision engines. This Leading Practice Brief is about how Morgan Stanley uses analytics and algorithms in support of a clear business strategy and empowers the entire organization to use analytics to make better business decisions.

The ever-growing volume of data challenges us to keep pace in ensuring that we use it to its full advantage. This research brief addresses the tools, technologies, methods and processes useful in designing a data program that is both relevant and actionable.

What is the value of analytics? This research brief discusses methods of assigning value to advanced analytics efforts and communicating it to stakeholders.

Inquiry:

One of our analytics challenges centers around data lineage and trust. People question where the source data came from and whether it’s trustworthy, which results in time-consuming traceability exercises to translate our results into terms that the end user can relate to. Is there a technological solution that can trace data lineage and reconcile data sources?