Introducing Quanta AI

Technology firms suffer constant margin pressure on products already on the market (in the sustaining life-cycle phase). Value engineering reduces product cost most commonly through component replacements, material changes and part eliminations. The value extracted does not impact core function; in fact, it often improves it. Value engineering projects have the most impact on a firm’s gross margins when bundled into a portfolio. Over time, portfolio returns are amplified as multi-year investments come to fruition. This is a key margin management lever.

Mark Streich and I met at the Thunderbird School of Global Management ten years ago. We recently reconnected at npv10 to champion Quanta AI in the technology sector. After finishing the MBA program, I spent five years as a value engineering fund manager for a Fortune 500 Silicon Valley company, and my work intrigued Mark, a serial entrepreneur and trained computer scientist in the Silicon Valley. He spent the past few years developing portfolio optimization AI for the oil and gas industry. In a single-click, executives can model hundreds of wells with differing production, investment and revenue streams to support decision making with data. He also tested his platform in real estate with top-notch results. A manually managed portfolio can be optimized by over 20 percent using this tool and approach to help guide strategy with data.

This proprietary platform is the bedrock for Quanta AI. We are targeting value engineering as it dovetails with our Silicon Valley experience. Additionally, Quanta AI can also support resource allocation for new product introduction, as well as research and development. If there’s a portfolio with multiple complexities and a myriad of variables, Quanta AI can optimize it. Astoundingly, large firms still rely on program managers using Excel to crunch large data sets. This approach is cumbersome, time consuming and futile as a method to capture the most valuable combination of projects.

Quanta AI incorporates all potential variables and provides optimum outcomes based on goals the investor wishes to model. Risk, predictive analytics and forecast variability are all incorporated into a single repository. The algorithms generate forward-looking data and metrics to determine if future investments are aligned with goals and resources. Savvy investors can decide—with a click—which investments to buy, sell or hold relative to a choice of financial targets (e.g. NPV, IRR, cash flow, debt to equity, payback period, etc).

In my value engineering portfolio management experience, we needed Quanta AI. Managing hundreds of investments with various return profiles manually is outdated, unnecessary and inefficient. As Mark says, “That’s what computers are for.” And that’s what Quanta AI is for.

Introduction to Portfolio Analysis for Oil & Gas

We have recently developed an introductory course for the Oil & Gas industry in partnership with PetroLessons.

Course Link

If you influence or make portfolio decisions for your company this course is for you!

Introduction to Portfolio Analysis illustrates the use of “portfolio analysis” to develop and compare alternative strategies that an O&G company might pursue. The examples included throughout the course show how projects and corporate performance measures interact and how the interactions create new opportunities for the corporation. The interactions can be quantified to allow decision-makers to compare alternate strategies and quickly assess the business performance trade-offs they will likely face when they select one strategy over another.

The course covers:

  • What is a portfolio?
  • Why use portfolios?
  • Typical corporate planning approaches
  • Portfolio planning
  • Ranking approaches
  • Rank-and-Cut Example using Excel
  • Multi-Factor Scoring Example using Excel
  • Integrated Optimization Example using npv10
  • Evaluating Portfolios
  • Creating forecasts
  • Using Generic Projects for Developing Strategy
  • Uncertainty in Oil & Gas
  • The Two-Digit Rule™
  • Reducing Uncertainty
  • Change Management 101
  • Change the Conversation
  • Goals and Constraints
  • Forecasts
  • Uncertainty

Who should take this course:

  • Financial Planning & Analysis (FP&A) Executives and Analysts looking for better approaches to corporate planning.
  • C-Suite executives needing to take a higher-level view of their company in order to make better strategic decisions and plan ahead for different scenarios.

Benefits/ Course Objectives:

Understand how using a portfolio approach to select projects and analyze different strategies can improve the organization’s performance, and how the culture may need to change to enable a better dialog between the financial planning team and the operating units. You will also see how using multiple forecasts, with probabilities, can enhance your insight into different strategies.