While giving customers what they want — and as rapidly as possible — may be a worthy goal for service organizations, Amy R. Ward at the University of Chicago’s Booth School of Business notes that businesses can’t always afford to do this. Her research uses probability to understand how best to align resources with customer demand and improve operational efficiency on a day-to-day basis.

Companies can monetize data internally to optimize operations and client services. They can also leverage that data across various client use cases.

Each month, the MIT SMR Strategy Forum poses a single question to our panel of experts in the fields of business, economics, and management. This month’s question asks our panel whether restrictions on skilled immigration in the United States will cause business to shift operations overseas.

Many of today’s most successful technology businesses— including Apple, Facebook, and Uber — are built on a platform-based business model. But the increasing popularity of platform strategies masks a difficult truth: Such strategies are hard to execute well, and they are prone to several common pitfalls. Those platform traps include growth with no strategic focus, pursuing an intermediate approach between the mass market and a niche, and overlooking the value proposition of partners.

Some industries like health care and retail are starting to see the transformational potential of big data and predictive analytics, but the cost of hiring skilled employees and the complexity of an extended supply chain network are daunting. New research suggests that the convergence of data science, predictive analytics, and big data have the potential to transform the way supply chains operate.

New product launches are highly complex and can pose major challenges to companies. But managing the interplay between product generations can greatly increase the chances for success.