Elements of Systematic
Planning
EPA's elements of systematic planning are
stated in Chapter 3 of the
EPA Quality Manual
for Environmental Programs and include:
- Identification and involvement of the project manager, sponsoring
organization and responsible official, project personnel, stakeholders,
and experts, etc. (e.g., all customers and suppliers). This element
ensures that the study will be designed to address the needs of all
vested parties (for example, data users, data generators, data analysts,
and other stakeholders). Consulting cross-disciplinary experts familiar
with the different technical aspects of the problem ensures that important
details of the study are not overlooked or ignored and technical challenges
will be addressed appropriately. It is also important to assign responsibilities
for the project so that conflicts can be resolved and progress is tracked.
For some projects, it may be most effective to create a formal "planning
team," while for others, one individual may be responsible for
the project and involve other individuals when necessary.
- Description of the project goals, objectives, and questions and
issues to be addressed. This element ensures that the participants
formulate a clear statement of the project's goals and objectives and
therefore understand the purpose of the project and expected results.
The objectives reflect a general statement of the intent of a project
and how that project is linked to addressing the environmental problem
(or contributing to the field of science). The project's questions will
define what data or information is needed to address the project's goals
and objectives. The transition from the project goals, to statement
of objectives, to specific and appropriate questions are some of the
most important steps in systematic planning.
- Identification of project schedule, resources (including budget),
milestones, and any applicable requirements (e.g. regulatory requirements,
contractual requirements). Identifying the available resources and
deadlines at the beginning of a project helps ensure the project is
feasible and timely. A clear statement of the project's resources, constraints,
and deadlines helps prevent potential issues and/or conflicts by determining
practical bounds on the project as early as possible. Regulatory, statutory,
contractual and other constraints should be considered that might affect
the project schedule.
- Identification of the type of data needed and how the data will
be used to support the project's objectives. This element focuses
on identifying the specific type of data or information needed to complete
the project. Types of, sources for, and how to obtain information needed
to address the study questions should be listed. Sources may include
literature, existing databases, and/or new data collection. By developing
a list of the information needed to address the project questions, the
project requirements will be clearly defined. In addition, the list
may identify other information that will be helpful, or that can be
economically collected to facilitate the use of the project results
for other purposes.
- Determination of the quantity of data needed and specification
of performance criteria for measuring quality. This element focuses
on establishing criteria to ensure that the information and products
generated meet the objectives of the project. These quality specifications
are established at both the product level and at the level of components
of that product, such as the quality of individual measurements. Examples
of product-level criteria include EPA's information quality guidelines
components -- objectivity, utility, integrity, and reproducibility.
Examples of component-level criteria are quality criteria for individual
measurements (for example, criteria for precision, bias, accuracy, representativeness,
comparability, completeness, and sensitivity) and criteria for decisions
or estimates [for example, a stated desired confidence that results
will fall within a specified window such as Type I and Type II error
rates (false rejection and acceptance error rates), uncertainty intervals,
etc.] After the information, data, or product is generated, these criteria
are used to determine if they met the project's objectives.
- Description of how and where the data will be obtained (including
existing data) and identification of any constraints on data collection.
This element focuses on how to amass the data or information needed
for a project by collecting new data, using existing data, citing
information from other resources, etc. When collecting new data or
information, consider where to collect samples (sampling design),
when, how to best acquire physical specimens of an adequate size and
dimension (sample support) to represent the variable of interest within
the sampling unit, questionnaires and survey instruments, sampling
technologies, analytical methods, representativeness, etc. When existing
data or information (i.e., from models, databases, literature, etc.)
is used, consider sources and methods for assembling it. Also consider
how the data will be inspected to ensure compatibility with the project's
goals and the handling of information/data either through physical
custody of samples or the entering of specific information into a
database or spreadsheet.
- Specification of QA and QC activities to assess the quality performance
criteria (e.g., QC samples for both the field and laboratory, audits,
technical assessments, performance evaluations etc.). It is often
necessary to plan ahead for QA and QC activities to ensure that a process,
item, or service is of the type and quality needed and expected by the
customer. QA and QC activities measure the attributes and performance
of a process, item, or service against defined standards to verify that
it meets the stated requirements. Example of these activities include
assessments/audits of field sampling and laboratory activities, QC samples
(blanks, duplicates, etc), project reports, and inspections/testing/maintenance
of equipment, supplies and consumables, etc.
- Description of how the acquired data will be analyzed (either in
the field or the laboratory), evaluated (i.e., QA review, verification,
validation), and assessed against its intended use and the quality performance
criteria. This element focuses on the reviews of both the information
(such as verification and validation) and the project (peer reviews,
clearance procedures, etc.). It is important to determine up front how
data and information will be summarized, displayed, and communicated;
how uncertainty in the information will be determined and accounted
for in the final product; and how the information will be used to achieve
the project's goals.
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