A message from Lakshmi Bloom:

2020 has certainly been a challenging year

As we look back over the year, we remain deeply grateful for the sacrifice of healthcare and frontline workers who made it possible for us to function and feel protected as we navigated through the pandemic.

Personally, I am also incredibly proud of the strength and resilience of the Data for Decisions team. They have met virtually and worked tirelessly without any loss of productivity, despite increased responsibilities at home and the ongoing uncertainty of what lies ahead. And they have continued to exude enthusiasm for our clients, our projects, our research endeavors and an unfailing commitment to the high standards we have set for ourselves.

At the start of the pandemic I adopted Mother Teresa’s advice: “Do small things with great love”, as a guiding principle for myself. It helped me focus my energy on the tasks at hand, the ones I could shape and control. I believe that the team at Data for Decisions does “all things with great love” and that great service to our colleagues and clients emanates from this.

The end of the year approaches, and it is time to look ahead to the new year! To our valued network of clients, colleagues and friends – on behalf of all of us at Data for Decisions - I extend our very best wishes for the new year. May you stay safe and be well, and find much happiness and success in 2021!

Seasons Greetings

Although it was virtual, the Data For Decisions team celebrated the holiday season together.

From our team to yours, best wishes for a lovely holiday season and a peaceful new year.

We are a Boston-based economic consulting group specializing in labor and employment, valuation and life sciences.

Our clients include leading law firms, Fortune 500 companies, not for profit organizations and government agencies.

We bring strategic insight, analytic rigor and clarity to complex issues and help our clients make informed decisions.

Data For Decisions

Practice Areas

Drawing upon well-established labor economics theory and methodologies, as well as the principles of statistics, we provide law firms and companies with sound economic analysis in several areas of labor and employment law.

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Honest and Unbiased Assessment and Analysis of Issues

Our reputation is built on fulfilling the promise we make to our clients: to deliver unbiased, fact-based findings which facilitate the decision-making process and help guide our clients to the appropriate actions.

Commitment to Protect Confidential Information

Much of the data we work with is confidential and needs to be handled with tremendous sensitivity. We understand legal concerns and are committed to work with the necessary care and deliberation. All information received by our office, regardless of the manner of transmission, is appropriately safeguarded. Any information that the law does not require us to keep on file is not retained.

What sets us apart from the rest?

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Unlike larger consulting firms, we are known for the personal involvement of our expert economists and statisticians at every stage of your project. From our initial meeting through issues assessment, analysis and strategic planning, our experts are with you. We do all the work ourselves, including report preparation and expert testimony.

We have particular expertise in the assembly and statistical analysis of data appropriate to assessing claims of age, gender, and race discrimination in employment. We also have considerable experience in the estimation of economic damages in employment discrimination and wrongful death litigation.

We are actively engaged in pioneering efforts to value vaccines, pharmaceuticals, and medical devices in ways faithful to well-established principles of finance and economics, and in line with new value-based healthcare initiatives. We seek to raise awareness about the appropriate use of benefit-cost and return-on-investment estimates in making rational policy decisions about including particular vaccines in national immunization programs and reimbursing their cost to end users.

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