Stock image of a beautiful young woman studying a see through computer screen contemplating

The Golden Rule: Bring the Data
W.E. Deming’s famous words, “In God we trust. All others must bring data,” isn’t just a witty joke—it’s the bedrock of any disciplined approach to problem-solving. Deming’s point illuminates the indispensable role of data, measurement, and analysis in evaluating current performance against pre-established standards. In essence, it’s the cornerstone for initiating any problem-solving journey.

The High-Stakes Endeavor of Estimation
But for those of us in cost, schedule, and effort estimation, it’s less of a journey and more of a high-stakes obligation. When it comes to Should-Cost, Price-to-Win, Supplier Assessment, Design-to-Cost, Bid and Proposal support, and ROM estimating—just to skim the surface of our professional canons—the faith we place in our estimates is unshakable only if the data underpinning them is irrefutable. Yet the sanctity of this data is not to be taken lightly; misuse or manipulation can lead us down the path of incorrect conclusions and costly mistakes. Therefore, safeguarding our data’s accuracy, reliability, and trustworthiness becomes paramount. As the gospel of The DoD Cost Estimating Guide says, “Data is the heart of the estimate. Identifying, collecting, validating, normalizing, and analyzing quality data influences the remaining steps in the cost estimating process.”

Challenges to the Creed
Despite the omnipresence of ‘big data,’ the journey toward systematic data collection and seamless accessibility is a formidable one. Achieving high-quality, structured data requires an investment of time, commitment, effort, and financial resources that many organizations are reluctant to make. Coupled with the inherent difficulty of the challenge, institutional zeal for this transformative endeavor is often in scant supply.

The stumbling block? Subject Matter Experts (SMEs). First, they’re time-starved. Every moment they invest in estimate generation is a moment they could have added value elsewhere. Second, many of these high priests of our data-driven creed are on the verge of retiring, taking their vast knowledge—our invaluable data—with them unless we capture it. So, how do we immortalize this expertise? By creating an easily navigable data repository that our cost estimators and engineers can turn to time and again.

Numerous authoritative sources offer insights into these data management best practices:

  • Cost Estimating Body of Knowledge (CEBoK and CEBoK-S) from the International Cost Estimation and Analysis Society (ICEAA)
  • Cost Estimating and Analysis Handbooks from NASA, Army, NAVSEA and other federal agencies
  • Government Accounting Office’s (GAO’s) Cost Estimating and Assessment Guide

 

The Sin of Bias
While our estimates are grounded in expertise, they’re not immune to inherent biases—both cognitive and organizational. Even seasoned SMEs, intimate with past failures, can find themselves in a situation where history repeats itself.

This failure to systematically harness past performance data and SME knowledge to inform estimates often leads to suboptimal proposals, eroding profit margins, and inaccurate independent cost estimates. Such an overreliance on the judgment of SMEs handicaps our ability to elevate historical data to the level of intellectual property. Consequently, even when organizations manage to archive this invaluable historical data, it’s often not in a form that readily lends itself to activity-based estimating.

Software as the Great Enabler
In abiding by our data-driven creed, parametric cost estimating software becomes indispensable. Take TruePlanning®, for example. TruePlanning® not only has nearly 50 years of cost research embedded in the model—it also serves as a framework that lets organizations leverage a centralized, structured repository of their own historical, technical, and programmatic data, all closely linked to actuals for more credible estimating.

So, in honoring Deming’s enduring wisdom, let’s ensure we bring the data. After all, “Without data, you’re just another person with an opinion”—a far cry from the data-driven creed that cost engineers should strive to uphold.