We build the model, you build the estimate.
Parametric estimating / modeling is our passion. A parametric estimate is a powerful tool to streamline your proposal development and budgeting process.
Parametric estimating employs techniques that analyze the relationships between a project’s technical, programmatic, and cost characteristics to build estimates. Cost engineers define these relationships as Cost Estimating Relationships (CERs), which use mathematical algorithms (or logic) to produce cost estimates.
How we work with you
We have designed and developed parametric cost models for our clients for over a decade. Every project is a challenge and the reward is in helping our clients plan beyond their current “cost horizon”.
1Kick-off & Requirements Definition
After you contact us, we’ll get in touch with you and cover some general information. We’ll then coordinate setting up an NDA (non-disclosure agreement). After the NDA is in place, we’ll assign an analyst with the requisite skills and experience to review your requirements and prepare a detailed estimate for our services.
Our analyst will continue to work closely with you (and approved subject matter experts) to gain an in-depth understanding of the technology or process we will be modeling for you. We will also define how you want to deploy the model: Excel, on the Web, in another tool via XML.
Once we have worked with you to define the requirements, we will start gathering cost and scope information to help us define a cost basis. This information may include data you provide or industry data available from other sources (e.g., RSMEANS unit costs). We will work closely with you to make sure these data fit within the defined scope of the model.
- Basic Accounting Records
- Cost Reports
- Historical Databases
- Technical Databases
- Other Information Systems
- Cost Proposals
After we collect the data, we will use regression analysis, along with other statistical and engineering analysis techniques and tools, to define the major cost drivers. These cost drivers will form the basis for the parameters we will include in the model.
At this point we have begun to define relationships in the data. Now we will begin to distill these relationships into algorithms. This is the meat of the process and, if the other steps are science, this would be the art.
By the end of this step will have the basic set of algorithms that define the model. We will begin to integrate these algorithms in the next step.
Each of the algorithms we just created roughly represents a parameter. We will begin to build the set of parameters that is the framework to store the model logic and handle the capture and processing of user inputs and model outputs.
Finally we work with the you to develop an interface for the model. This step is critical to make sure the model parameters are clear and the user interface is simple.
At this stage you will be start beta testing the model and we will address any functional use case concerns. Our goal is to give you a straightforward model you understand.
Verification, Validation & Testing: We perform verification of all cost models we develop for our clients to confirm intended model performance and resolve any adverse model behaviors. We will include documentation with each model for testing and verification activities, cost model changes, and issue resolution.
Deployment: We design the model so that you can use them in a number of tools. Excel, on the Web (via IDEAL), or integrated into a custom system via XML.
How Parametric Estimating Can Help Your Business
There are many application for parametric estimating, including proposal development. In fact, you can save an estimated 40 to 80 percent during proposal preparation by using parametric estimating in place of a “normal” bottoms-up approach¹. This is, in part, because parametric estimating is one of the most effective estimating techniques during early, conceptual design, phases. Also, parametric estimates are ready in a matter of minutes and adjust well to scope, technical and performance changes.
- Life Cycle Cost Estimates
- Unfunded Liability Estimating
- Budget Planning Analysis
- Risk Analysis
- Sensitivity Analysis
- Conceptual Estimating
- Independent Cost Estimates (ICEs)
- Estimates at Completion (EACs)
- Basis of Estimates (BOE’s)
- Costing by Phase of Contract
- Cost Spreading
- Design-to-Cost (DTC)
- Subcontractor Price or Cost Analysis
- Proposal Evaluation
- Bid/No Bid Analysis
- Forward Pricing Rate Models
- Cost as an Independent Variable (CAIV)
- Should Cost Studies
- Trade Studies
- Cost Realism
- Software Sizing parameters
- MTBF, MTTRs
- Make-buy analysis
CERs are parameter-driven cost algorithms that calculate costs based on user input and are the foundation for building a parametric cost estimate. We derive CERs from statistical analysis of historical project cost data and other validated sources and compiled into mathematical equations using a proprietary procedure.