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.

What DOES That Logo Mean?

Our first logo is the mathematical formula for calculating the Net Present Value of Cash Flows (CF), using a discount rate of 10%, or as often called in industry, “npv10.”

The symbol Σ means to sum all the values in the series represented on the right.  Although I don’t include the bounds, they are often assumed to be from time period zero (initial investment) through some future time period.  CFt thus representing the cash flows for time period t.

The divisor is 1.1t, while the general formula should be divided by (1+i)t. As I named the company npv10, I just assumed the interest rate i was 10% or 0.1. For time period zero the divisor is 1.10 (equals 1), for time period 1 it is 1.11 (equals 1.1), and so forth.

But why the NPV of Cash Flows?  Why not NPV of Net Income or Revenues or EBITDA, or use IRR (Internal Rate of Return)?

The NPV of Cash Flows has been found to be a good way to compare projects to one another, and take into account the timing of the cash flows to the company.  Earning money back sooner is more valuable to earning the same amount later.

But the software does not compare projects against one another according to their individual NPV.  A number of successful companies do that, but they’re missing out on a number of important points:

  • Projects do not exist in isolation.  They compete for limited resources with other opportunities, so they are all interrelated even if not obviously so.  (See the example I did for a technology company.)
  • Projects may directly depend on other projects.  For example, an oil company may drill a test well, and the result of that test may determine how many other producing wells they drill in the area.  The test well is not expected to produce any return, so it has a negative NPV.  But if the test is positive, each of the production wells can move forward, producing positive returns.  Our software enables you to directly connect one or more projects, so selecting one or more producing wells (with positive NPV) requires that the associated test well (with negative NPV) is also selected.
  • Timing matters.  If you are attempting to manage the company, and it selects nothing but projects with large NPVs, where the positive cash flows are in the distant future, you will need cash to sustain you until those start returning cash.  This is why I often recommend setting minimum goals for Cash balances, to ensure the company survives any periods of low cash flow.  In this way, the software may select projects with smaller NPVs first, because they may return cash sooner, and that can be put back into funding the larger projects later.

The final point I wish to make is that while I named the company after a useful calculation, the software allows you to set goals and constraints on almost any of your metrics and KPIs, and decide which one you wish to maximize or minimize for each analysis.  You may wish to maximize Revenue, Production, or Revenue, or minimize Capital Expenditures, or Marketing Expenses, to see how you can best achieve your strategy.

As your company figures out which goals, constraints, and optimized metrics most matter, you will get the most value for your company, and help it develop its strategy and plan for the future.

Hello world!

It is finally time to hang my shingle out, and let the world know what I have been up to for the last 5 months.

I’ve been attempting to solve that formula at the top of the page…

Okay, that’s actually just PART of the formula.  The actual formula is far longer, and it is just one of many other formulas that must be created and calculated.  This goes part of the way towards explaining why not everyone is doing this. It is not easy.  But solving thousands of simultaneous equations is not what I am ultimately trying to accomplish.

I am making it far easier for companies to quickly evaluate their strategic alternatives, in terms of financial and operational performance.

As the software progresses, I will share more details.

For now, just know the answer to the equation was 728. That wasn’t so hard, was it?