In a deeply meshed business environment, it is often difficult to balance span and depth when evaluating the impact of a resource planning strategy. DecisionFlow offers a broad range of professional services expertise coupled with breakthrough analytics to facilitate this process.

Our holistic approach, a blend of business proficiency, advanced mathematical modeling and artificial intelligence methodology, brings clarity to some of the most complex business decisioning problems.

A key aspect of successful decision management is to identify critical drivers and separate them from secondary requirements, a skill we have honed over years of combined business and analytical consulting experience.

Often, these requirements are not easily separable, however. They form a dense mesh of intricate logic that may extend deep into core company processes, and it is important to capture requisites that are strongly correlated as a whole while setting aside elements that are unlikely to impact the bottom line.

This is what we have coined the dendritic modeling approach to decision modeling, a unique enabler of the competitive time-to-value we offer.

DecisionFlow generates client-focused solutions with the help of an analytics framework developed internally for nearly a decade. This analytical core is formed of two specific components:

A library of mathematical modeling lego “bricks" that can be assembled quickly and efficiently to form a customized prescriptive analytics model that is unique for each customer.

A simulation framework based on a mix of exact algorithms, commercial mathematical programming libraries and proprietary machine learning heuristics, that sources the customized models and returns a solution profile rapidly and accurately.

A sampler of our application taxonomy:

Investment and Finance
Merger and acquisition
NPV, discounted cash flow optimization
Capital budgeting

Executive Management
Reconciliation of business strategies across business units

Product Management
Product portfolio management in competitive and cross-elastic frameworks

Sales and Marketing
Order management
Market segmentation
Target price analysis

Engineering
SKU stack optimization

Operations
Line/logistics push-pull optimization
Sourcing, inventory management

The DecisionFlow analytics framework natively handles many different types of resources, including:

capital
assets
products
finished or partially finished goods
tier-N supplier products
competitive technology and/or products
plants, space, equipment
raw material
natural resources
staff and services
real estate assets

A typical short-term engagement cycle:

Assessment and data needs evaluation -2 to 4 weeks
Pilot -3-5 weeks
Analysis and validation -2-3 weeks

leads to an actionable solution in as little as two months.

A broader engagement consists of the following steps:

analysis
simulation
internal acceptance
deployment
training and support

Among more than 60 completed projects, we can highlight:

Generated ROI of over US$90 millions/year for a Fortune 500 chemical manufacturing company, meeting the key challenge of integrating a complex chemical production mass balance model into a strategic supply chain optimization framework.

For a major semiconductor manufacturing company, built a robust production-distribution planning simulation tool to balance 30 product lines over a 3 year forecast horizon and evaluate executive planning scenarios in near real-time.

For a holding company of baked goods manufacturers, quantified merger & acquisition scenarios by simulating joint operations under capital expenditures and restructuring options, resulting in an annualized operating cost reduction of US$ 55 millions.

For the regional government of Lambayeque Province, Peru, built a land auction optimization framework used in real-time to generate net proceeds of US$ 150 million, a 50% improvement over the manual selection of winning bids.

Contact us for additional references.

Jean-François Pusztaszeri
_{Chief Executive Officer}

Jean-François Pusztaszeri is the CEO of DecisionFlow, guiding the company’s vision to deliver advanced analytics- and AI-enabled evolutionary resource planning systems. With over 25 years of experience in operations research and analytical consulting, he has led projects across industries including semiconductors, finance, manufacturing, transportation, and telecommunications. Jean-Francois has worked with global firms such as IBM, Toyota, American Airlines, and Cargill.

Earlier in his career, as lead scientist at CERN, he pioneered the use of combinatorial optimization in high-energy physics. Jean-François holds a Ph.D. in Mathematics from ETH Zurich, has published 95 peer-reviewed papers, and co-authored a book on nonlinear optimization.

Sanjay Saigal
_{Chief Operating Officer}

Sanjay Saigal is the COO of DecisionFlow, overseeing operations and client success across the company’s offerings. He brings over 30 years of experience in consulting and entrepreneurship, having led high-impact initiatives for Fortune 500 companies and startups in sectors such as supply chain, transportation, and retail. Prior to DecisionFlow, Sanjay founded several analytics ventures and held senior roles in business consulting.

In academics, Sanjay taught and served in the leadership of Stanford University’s Institute for Computational & Mathematical Engineering and UC Davis’s Graduate School of Management. Sanjay holds a Ph.D. in Computational and Applied Mathematics from Rice University and B.A. Honours in Mathematics from St. Stephen’s College.

Ed Rothberg
_{Chief Technology Officer}

Ed Rothberg is the CTO of DecisionFlow, leading the development of next-generation optimization- and AI-driven planning tools. He brings over three decades of expertise in algorithm design, solver development, and optimization modeling. Ed was co-founder and CEO of Gurobi Optimization, where he continues as Chairman of the Board. Under his leadership, Gurobi became an industry leader in mathematical programming software. Previously, Ed led the CPLEX R&D team at Ilog, where he also built semiconductor fab scheduling applications.