We are the first technology
consultants that
understands “the business of behavior change”
. Communicate, train,
measure and reward your people for embracing the system that is
the lifeblood of your business and future.
CBEF
Calculation Process
The goal of our Custom
Behavior Execution
Framework (CBEF) is to produce a prioritized listing of behavior
results and issues to be mission critical for the organization. In order to provide an objective, quantifiable result, the
following methodology has been developed to complement and extend
the CBEF development process. If it is within the budget and
timeframe constraints, at least two different versions of this
matrix should be developed by different people, starting with
identical audiences, intents, experience requirements and
functional descriptions, but performing the rankings
independently. These two results can then be averaged to produce
results with greater confidence.
This list is highly useful in determining
what features should be included in a base system design and
implementation and defending those decisions with the company with
specific numbers. Features high on the priority list can be
suggested for the current initiative while features lower on the
list can be slated for future initiatives. If a Feature ranks high
on the list but is clearly excluded from the current initiative by
a factor such as cost, the result may be interpreted as a strong
argument for its implementation in a timely new initiative.
Multiple models created by different people
can be averaged to provide even stronger results, or if desired,
they can be presented separately, to either emphasize or
de-emphasize differences of opinion on a particular project.
The CBEF matrix is a grid with Audiences in
the vertical axis and Intents on the Horizontal, as shown below.
Black cells indicate no correspondence between audience and
intent.
Step 1 –Ranking and Assigning
Values to Audiences
The CBEF matrix is a grid with Audiences in
the vertical axis and Intents on the Horizontal, as shown below.
Black cells indicate no correspondence between audience and
intent.
|
Money or points |
Training |
Games |
consumer |
|
|
|
employee |
|
|
|
business |
|
|
|
Audiences are then ranked according to their
importance to the company or to the behavior results being developed. Each audience is assigned a value from 10-1 with 10
representing the most important audience, and 1 the least
important. If there
are fewer than 10 audiences, which there usually are, the
numbering will stop short of one (i.e., 10, 9, 8, stop).
|
|
Money or points |
training |
games |
10 |
consumer |
|
|
|
9 |
employee |
|
|
|
8 |
business |
|
|
|
Intents are not ranked or assigned values.
Step 2 – Adding Behavior Results to the Grid
Behavior results are developed for each
Audience/Intent combination in the grid as shown below. These are high-level objectives that have been identified
during interviews with the client and the client’s people,
industry research and competition research.
|
|
Money or points |
training |
games |
10 |
consumer |
Hedonic rewards |
Educate and grow more distributors |
|
|
|
|
9 |
employee |
|
Six sigma cert. |
. |
|
|
|
8 |
business |
|
Product certification |
|
|
|
|
Step 3 – Adding Features to the Grid
The next step is to expand the behavior
results with more specific
features which may be implemented on the participant. Great care should be taken to ensure that consistent
language is always used with the features, especially across
intents. Ideally, a
listing of potential company features should be developed
separately before plugging them into the grid.
Example: if using the term “Location
Search” to describe a feature that would provide the ability to
search for business locations, always use “Location Search” to
describe this feature, don’t switch it to “Search Locations” when
moving from one audience or intent to another.
The grid should be expanded as shown below.
|
|
Money or points |
Training |
games |
10 |
consumer |
. |
. |
|
|
|
|
|
|
|
|
|
|
9 |
employee |
|
|
|
|
|
|
|
|
|
|
|
|
8 |
business |
|
|
|
|
|
|
|
|
|
Step 4 – Ranking the Features
The next step in the process is to rank the
features by the Return that they will provide to the participant if implemented .
Cost/Benefit analysis should be
performed for each Feature. A value of 1-5 is assigned to both the Cost (1 = Low Cost,
5 = High Cost) and the Benefit (1 = Low Benefit, 5 = High Benefit)
of each feature. The
result of Cost/Benefit (Cost divided by Benefit) will provide a
numeric value for each Feature with low values identifying the
most cost effective (greatest Return on investment), and high
values identifying less cost effective items (less Return on
investment). Features that have identical Cost/Benefit should be
ranked subjectively based on an ‘educated guess’. The Cost/Benefit
analysis is only a guideline, not a hard and fast rule. Some items in any system may need to be developed
regardless the Cost/Benefit analysis results.
Example Cost/Benefit analysis for the
Companys/Buy Products Features:
Money
or Points- web user interface combing all systems
Cost = 4, Benefit = 4, Cost/Benefit = 1
Training: -rapid web based online training extranet
Cost = 1, Benefit = 4, Cost/Benefit = 0.25
Games–
warehouse MGT barcode system
Cost = 5, Benefit = 2, Cost/Benefit = 2.5
Thus the Return ranking created for these
three Features would be:
Training (0.25, most cost effective)
Money or Points(1)
Games(2.5, least cost
effective)
|
