A DEVELOPMENTAL-GROUP MODEL FOR BANK FORECASTING
BY
S.L ADEYEMI Ph.D
UNIVERSITY OF ILORIN
ABSTRACT
The object of this paper is to develop, illustrate and critically analyze a developmental group
forecasting technique, which shows great potential as an analytical tool in the current bank
environment. Correctly utilized, the technique should allow for improved planning and
profitability through the optimal use of bank resources.
INTRODUCTION
Forecasts are needed to predict future event in any organization. A sound forecasting system
result into competitive advantages. Most importantly is the ability to foresee changes in relevant
environmental correlations which affect profitability (For instance, changes in consumer
preferences, uncertainty in investment molests and increase loan competition) and to construct
goals and plans accordingly. Most writers have emphasized that forecasting systems are essential
when the environment is undergoing rapid change, a situation which is descriptive of today’s
banking environment. So in a rapidly changing situation, prediction becomes increasingly
difficult. As a result, a variety of techniques have been developed to aid the bank manager with
forecasting problems.
Available forecasting techniques fall in two broad categories- those, which rely primarily on
statistical or mathematical models, and those which, rely on group or individual processes. The
most common formal forecasting systems rely on the use of mathematical models for various
reasons including relatively low cost per forecast, minimal time involvement and perceived rigor
involved in the model (see Chambers, et. al. [1974]. Recent advances in group structures and
process as well as group decision making skills may, however, allow the group approach to be
competitive with the statistical routines in certain situations (see Drandell [1975]).
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THE ROLE OF FORECASTING IN THE PLANNING PROCESS
It is important to distinguish between a forecast and such terms as goals, strategies and plans.
Figure 1 presents the relationship among these variables. A forecast, according to this
framework, is defined as the future level of the particular variable, which we are trying to predict
if management takes no new action, i.e., if management maintains its current course. Objectives
and goals represent future desired states which management would like to attain. If there is a
difference between the forecast and objectives, it represents a planning “gap” which calls for
development of plans and strategies to attain desired future performance. Viewed in this manner,
forecasting is vital to future success. For example, goals may be unrealistic in light of future
conditions. On the other hand they may be overly conservative. As Figure 1 indicates,
forecasting is equally applicable to internal and external factors, although it is usually associated
with external factors.
THE FORECASTING MODEL
The procedure described here for generating a forecast relies on a highly structured group
process
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Figure 1.
Relationship Among Forecasting, Goals and Plans
Environmental
Analysis and
Forecasting
………………….
A. External
B. Internal
Development of
objectives and goals
……………………
A. External
B. Internal
Problem Identification
and Analysis
“Gap”
A. Development of
Strategies (Plans) to
Reduce the Perceived
Gap
B. Modification of Goals
imbedded within a developmental forecasting model. The group process relies on techniques,
which enhance both the quality and acceptance of the group decision. The developmental
forecasting model is a series of logical decision steps leading to prediction of the future level of
the variables in question.
The developmental forecasting model relies on combining historical and future data in a logical
sequence. As a first step it is necessary to identify those factors, which influence the forecast
(both historical and foreseen future factors). In most bank situations, these factors can be
subdivided into two categories – environmental (external) factors and management policies
(internal) factors.
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Second it is necessary to determine the relative importance of these variables. This is usually
done by rank ordering the list generated in step 1 from most to least important. The third step in
the forecasting model is to determine which of these factors will change in the time horizon of
the forecast. When steps 2 and 3 are combined, the rationale becomes apparent; a change in a
relatively important factor will have a greater impact on the forecast than will a change in a
relatively unimportant factor. The order of steps two and three is also important because it is
necessary to determine importance independently prior to change. There may be a tendency, if
the steps are reversed, to identify those factors which will change as those which are important.
The fourth step of the sequence is to determine the impact of the change – positive, negative or
zero. Finally, this information is combined and a forecast is generated based on current position,
forecasted changes and their associated impacts.
In addition to the generated forecast, a working “model” for management of the forecasted
variable is generated since the factors which affect the variable have been logically determined.
When combined with the group process presented in the next section, each manager becomes
aware of those factors which should be considered in the daily use of the forecast.
GROUP PROCESS
The forecasting model presented in the previous section listed five steps, which require
determination of the importance and impact of factors influencing the forecast. This
determination is made through a structural group process for eliciting and evaluating ideas. This
group process relies on four elements of problem solving and decision-making. The first, a
creativity or fact-generating phase, is associated with generation of ideas about the problem. A
number of group researchers (Janis [1972]) point out that individual work may be better suited
for this phase. The second phase, screening or evaluation of ideas once they are generated, seems
to be enhanced through the interaction of group members (Maier [1963] and Nutt [1976]). It is
suggested, then that the group process should allow for different procedures for each of these
phases.
Third, it is important to maximize the acceptance of the group forecast if each member is to
utilize the generated forecast effectively on an operational basis. In general, acceptance is
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enhanced through participation. It is essential, therefore, that the group process maximizes input
from each member of the group.
Finally, it is important to reduce dominance by certain members of the group, especially those
with higher legitimate authority; it is important to arrive at a forecast which is accurate and based
on factual information rather than one which reflects opinions of group members.
Given these four elements, a group process was derived to achieve each of the steps in the
forecasting model. The steps in the group process and rationale for each are presented in the
following paragraphs. An application in forecasting commercial loans follows the discussion.
Step1: Presentation of the forecasting problem to the group. Before the group actually convenes,
it is important to define the forecasting problem accurately and concisely. Although the group
leader needs not be an expert in the problem area, obviously such a leader must be an expert in
the group process. If this is the case, then the problem should be defined prior to the group
meeting by line management. Some guidelines for stating the problem have been determined in
empirical research (Maier [1963]). It is important to state the problem briefly in impersonal
terms in order to avoid premature bias. In other words, solutions should not be suggested at this
stage. Second, demonstrate that the problem is related to the interests of the group. In many cases
this is not necessary because the group members will work on a daily basis with the forecast.
Step 2: Generation of ideas. Historically, the idea generation phase has relied on techniques
which attempt to maximize creativity through synergy (brainstorming) or which attempt to avoid
the inhibiting effects of direct person-to-person contact (Delphi techniques). Recent research
(Sackman [1975]); and Delbecq, Van de Ven and Gustafson [1975]) has indicated that positive
aspects are definitely forthcoming from having group members in direct contact but that it is
essential to structure this interaction. For this reason, the group forecasting procedure relies on
the silent generation of ideas by group members in writing. Advantages of this technique include
motivation from the group setting, allowance for time for thought and recall, problem focus and
avoidance of premature evaluation of ideas (Delbecq et.al. [1975]).
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Step 3: Recording of ideas for the group. Research has shown that the simple act of recording
ideas has a significant impact on the quality of the group decision (Maier [1963]). The method of
recording should promote equity among group members while not weighing any idea more
heavily than another (at this point there is no reason to assume that one idea is any better than
another). The round-robin recording method of Delbecq et.al. seems to meet both of these
criteria. Ideas are presented one at a time by each group member and recorded by the leader until
all ideas have been recorded. In line with the original brainstorming literature, additional ideas,
which, arise through “synergy” may be added to list and presented in turn.
Step 4: Discussion of each alternative idea for clarification. The key here is to present as
objectively as possible the rationale for each idea; clarity is the goal. The function of the leader is
to guide the discussion to ensure that ideas are understood by each of the group members. In
actual practice, it is inevitable that participants will attempt to bias the group toward those ideas
that they have suggested. This may be minimized by the leader continually focusing on the
clarification issue.
Step 5: Evaluation of the ideas presented. At this point, it is necessary to reach some conclusions
concerning the factors presented so far. Normally this is done through a discussion process. Open
discussion, however, has several drawbacks, which may lead to lowered quality of output. First,
members may feel inhibited, especially if persons higher in legitimate authority are present.
Second, differences in verbal skills may unbalance the final group product. Finally, the rationale
of the process may b e questioned by some members (due to unequal participation) and therefore
the final group product may not be accepted and used on the job. For these reasons, the silent,
democratic voting procedure (Delbecq, et.al. [1975]) is used here. Advantages of silent voting
include equal participation and weighing of all members ideas, relatively independent judgments
and increased acceptance of the final vote. The decision then, is the mathematically derived
mean of the group members’ individual judgments.
This structured group process is utilized in each of the five steps of the forecasting models; five
iterations of the process are undertaken for each forecast, which is made. Although the group
process may appear to stifle group social needs, it is important to remember that the social
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functions of the group (which normally occupy about 50% of the group’s time) will still take
place, although probably to a lesser extent. What this structured process does is to allow the time
spent on the task to be extremely efficient and productive. In this way, the total amount of time
spent by the group is reduced considerably while the quality and acceptability of the forecast are
increased. The next section describes an application of the technique in a typical bank
forecasting problem, forecasting commercial loan levels.
AN ILLUSTRATION OF THE TECHNIQUE
In the Spring of 1977, the previously described development group forecasting technique was
field tested in the home office of an eastern metropolitan bank. The bank account selected for
forecasting purposes was the level of commercial loan volume. In order to obtain relatively quick
feed back on the usefulness of the system, forecasts were made for one-month periods only
(March and April). Obviously, such short-term forecasts are of limited value in practice.
(Recommendations for the optimum time horizon are included in the discussion section.) For
comparison purposes, a statistical forecasting procedure (Box-Jenkins) was used to predict
commercial loan levels for the same time period. As a further test, individual knowledgeable
staff was allowed to modify the statistical projections based on additional market information.
The results of the group technique can, then, be compared to statistical and modified-statistical
results.
Following approximately 20 hours of preliminary briefing and problem discussion at the bank, a
group was formed for the test. Five bank managers from commercial loans, the controller’s
office, and upper middle-level line management were involved in the forecast group. The
problem was defined for the group at the beginning of the meeting.
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Figure 2. Initial List of Environmental Factors.
1
Economic recovery
2
Projected availability of funds
3
Market demand*
4
Quality of our banking services relative to competitors
5
Income tax obligations in March and April
6
Market interest rates
7
Local prime rate
8
Corporate bond rates*
9
Tax exempt bond rates*
10 Consumer spending/debt
11 Stockholder reaction to loan/deposits ratio*
12 Seasonal inventory movements
13 Correspondent bank participation
14 Federal reserve policy
15 Capital expenditure activity
16 Real estate activity
17 Weather, etc*
18 Consumer debt*
19 Special local conditions – strikes, weather, riots, etc
20 Tax rebate and timing
*Eliminated or consolidated during discussion
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Figure 3. Categorized List of Environmental Factors
I
Cost and Supply of Funds
Projected availability of funds
Correspondent bank participation
Tax rebate and timing
Federal Reserve policy
II
Price and Demand of Funds
Income tax obligations in March and April
Economic recovery
Market interest rates
Consumer spending
Seasonal inventory movements
Capital expenditure activity
Real estate activity
Special local conditions
III
Competition
Quality of our banking services
Local prime rate
In addition, the steps, rationale and procedures of the group forecasting techniques were
discussed to alleviate any ambiguity that was present. It was suggested, and the group confirmed,
that two different sets of factors – environmental factors and management policies and objectives
appeared to influence the future level of commercial loans. Environmental factors were
arbitrarily selected first for discussion. Figures 2, 3 and 4 give the results for the generation of
environmental factors. Figure 2 presents the list of environmental factors recorded during step 3
of the group process following silent, written generation by the group members. During step 4,
clarification of ideas, it was decided that this rather cumbersome list of factors could be reduced
by grouping into three categories. Some factors, as indicated, were consolidated or eliminated.
Figure 3 gives the categorized list of environmental factors. Working conditions for each factor
was determined during this phase. Following discussion, it was necessary to determine the
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relative importance of the environmental factors, and this was done through the silent voting
procedure (step 5). Figure 4 presents the results of the voting with eight factors emerging as
important.
A similar procedure was followed for management policies and objectives. Figures 5, 6 and 7
present the results for management policies. Figure 5 is the consolidated list generated during the
fourth step, discussion. Figure 6 presents the actual voting (silent) for each of the factors. Figure
7 is the final list of management policies, which were generated through the group procedure.
Generation of these two sets of factors (environmental and management) required approximately
90 minutes.
At this point in the process, the group had accomplished a great deal. Most important, a “model”
had been generated for management of commercial loans. The implications of this are
considerable. First, since each member had an input to the result, the model was likely to be
understood and applied by each in practice. Second, the discussion proved useful in uncovering
potential conflict areas in the bank. Finally, managers became consciously aware of what factors
were being considered in managing this account by others in the bank.
The group procedure was again utilized in step 3 and 4 of the forecasting process, to determine
those factors that would change for the coming month and to determine the relative impact
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Figure 4. Identification and Relative Importance of Environmental Factors which will
Influence Commercial Loan Volume
Factors
Relative Importance Between Classifications
Relative Importance Among
Classifications
I. Price and Demand for Funds
II.
1
1.
Market interest rates
1
2.
Seasonal inventory movements
2
3.
Income tax obligations
3
4.
Economic recovery
4
Cost and Supply of Funds
III.
2
1.
Projected availability of Funds
1
2.
Federal reserve policy
2
Competition
3
1.
Prime rate
1
2.
Quality of banking service
2
Figure 5. Management Policies and Objectives which Influence Volume of Commercial
Loans
I. Liquidity Consideration
II.
III.
1
Loan to deposit ratio
2.
Current commitments
3.
Capital assets ratio
Income considerations
1.
Interest rates
2.
Credit standards
3.
Income needs
4.
Mix of assets
5.
Loan level objectives
Marketing effort
!.
Marketing program
2.
Marketing opportunities
3.
Manpower assignments
4.
Aggressiveness
5.
Management monitoring incentives
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of these changes. All five steps of the group process were followed. Figure 8 lists the results for
March. In the following month, the entire procedure was repeated. Factors determined to change
in April and their associated impacts are also listed in Figures 8.
Given this list, the group was then asked to generate a forecast for the coming month. As a base,
six years (month-by-month) data on commercial loan levels were provided. Statistics on each of
the variables from Figure 8 were not made available to the group. Each group member silently
generated a forecast, the individual forecasts were averaged, and the results (mean and range)
were immediately fed back to the group. The forecast used for comparison purposes was the
group average
RESULTS
Figure 9 present the comparative results for each of the one-month forecasts. (The level for
February had been 248 million and loan volume had plateaued at this level for several of the
previous months) As the figure indicates, the group forecast a loan volume substantially above
previous levels and its forecast was extremely accurate. Statistical and modified statistical
forecasts were conservative. For April, the group forecast predicted a similar marked increase in
loan volume. Statistical and modified statistical were again more conservative, and for this
month, more accurate.
DISCUSSION
These results suggest advantages and disadvantages associated with the use of the developmental
group approach. Most important, the technique is appropriate in those situations where there is a
complex, changing situation to forecast, where the forecast is non-routine and
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Figure 6. Voting Results for Management Policies that Influence Current Dollar Volume of
Commercial Loans
I. Liquidity Considerations
II.
III.
3-2-3-3-3 =14
1
Loan to deposit ratio
3-3-3-3-2 =14
2.
Current commitments
2-2-2-1-3 =10
4.
Capital assets ratio
1-1-1-2-1 = 6
Income considerations
1-3-2-2-2 = 10
6.
Interest rates
3-2-2-0-3 = 10
7.
Credit standards
2-3-3-2-0 = 10
8.
Income needs
0-1-0-3-0 = 4
9.
Mix of assets
0-0-1-1-2 = 4
10. Loan level objectives
1-0-0-0-1 = 2
Marketing effort
2-1-1-1-1 = 6
!.
Marketing program
2-2-1-0-3 = 8
6.
Marketing opportunities
0-1-3-3-0 = 7
7.
Manpower assignments
3-0-2-2-0 = 7
8.
Aggressiveness
1-3-0-1-2 = 7
9.
Management monitoring incentives
0-0-0-0-1 = 1
Figure 7. Relative Importance of Management Policies which Influence Commercial Loan
Volume
Factors
I. Liquidity Considerations
1
Loan to deposit ratio
2.
Current commitments
5.
Capital assets ratio
II.
Income considerations
11. Interest rates
12. Credit standards
13. Income needs
14. Mix of assets
15. Loan level objectives
III.
Marketing effort
!.
Marketing program
10.
Marketing opportunities
11.
Manpower assignments
12.
Aggressiveness
13.
Management monitoring incentives
Relative Importance
Among Classification
1
Relative Importance within
Classification
1
2
3
2
1
1
3
3
5
3
1
2
2
2
5
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where pooling of diverse information is required. On the other hand, the group forecast should
not be used for routine forecasting problems where relationships are well established or where
the relationship/problems are relatively simple. In these situations the statistical forecasting
methods are more efficient and more accurate. Where change is part of the managerial situation
(as in the commercial loan forecasting problem described in the previous section) utilizing the
abilities of skilled managers in a structured format may yield better results than those techniques,
which rely on historical information.
There are some cost/benefit tradeoffs involved when using the technique. On the one hand, the
group process is time consuming (about 90 minutes per forecast based on my experience)
Figure 8. Factors Forecasted to Change
In March
Influence on loan volume
Availability of funds
Undetermined
Current commitments
Positive
Income tax obligations
Positive
Seasonal inventory
Positive
Economic recovery
Positive
Market interest rates
Positive
Local prime rate
Undetermined
In April
Economic recovery
Positive (extremely)
Seasonal inventory
Positive
Current commitments
Positive
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Figure 9. Comparative Results for Group, Statistical and Modified-statistical Forecasts
March, 1977
April, 1977
Group forecast
254.5 million
261.8 million
Statistical forecast
249.3 million
258.5 million
managerial modifications
249.0 million
259.9 million
Actual
255.0 million
258.9 million
Statistical
forecast
with
when compared to statistical forecasts. Further, the group technique is usually limited to one
forecast per session. On the positive side, the group technique allows for increased understanding
of the variables affecting the forecast and maximizes participant interest in the process. Further,
understanding forecast rationale, purpose and process is enhanced through increased
involvement and commitments.
In the training area, the group technique has distinct advantages. While it is true that an “expert”
and nonvested leader is required, which may necessitate the use of outsiders or specially trained
staff, the technique is especially effective in team building and conflict resolution because
organizational problems are solved in group settings which require interaction and cooperation.
New members especially benefit from the instructional nature of the experience.
RECOMMENDATIONS FOR IMPLEMTATION
In implementing the group forecasting technique, bank managers should be aware of a number of
considerations which may influence the success of the forecasting program. I have found that
quality of the forecast is enhanced when the group is composed of members from different areas
of expertise relevant to the forecast. Further, the group members should be from an appropriate
level in the hierarchy; forecasting is a line management function. Staff-generated forecasts are
likely to achieve less acceptance (and usefulness) among the management team than those
generated as part of the line activity (Cleland and King[1974]).
A number of group process considerations are also relevant. It is important to try and keep the
membership of the group fixed for the duration of the forecasting process. Further, try to involve
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those with a stake in the forecast. An advantage of the group technique described here lies in its
ability to coordinate different perspectives and pool them for an accurate forecast. Since
commitment of group members is imperative, it is important to compose the group of members
with an interest in the forecast, such as those involved in the planning process. A function of the
leader is to define the problem for the group before the group convenes. “What are we
attempting to forecast?” is a problem that should be defined by management. Results show the
five-step group forecast process to b e much more efficient under these conditions.
In terms of content factors the optimum time horizon for the forecast should be determined, i.e.,
for what length of time is the forecast to be generated? Normally, this would correspond to the
bank’s planning cycle. This research has also shown that creativity in the group is maximized if
historical input to the group is kept to a minimum. If members are given a large amount of data
relating to the forecast based on what happened in the past rather than considering the factors,
which are anticipated to affect the forecast in the future.
In summary, the costs and benefits of several forecasting techniques should be weighed before
deciding on the technique to be used. A number of questions can aid in this analysis. What is the
purpose of the forecast? The previous discussion has tried to emphasize that the group
forecasting approach has several advantages, which are not forthcoming when statistical,
routines are utilized. What is the cost of being inaccurate? If this cost is high, then multiple
techniques might be employed to achieve a better “fix” of the forecast. Can the past be used to
estimate the future? In many bank situations today the answer to these questions is a probable
“no”. In these conditions of rampant change, the developmental-group forecasting process has
some distinct advantages as demonstrated by the described commercial loan-forecasting
program. This group approach, then, is one important addition to the bank manager’s battery of
forecasting techniques.
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REFERENCES
Anderson, C. R. and F. T. Paine, “Managerial Perceptions and Strategic Behaviours,” Academy
of Management Journal vol. 18, (November – December, 1975) pp. 811-823
Chambers, J.C., S. K. Mullick and D. D. Smith, “How to choose the Right Forecasting
Technique,” Harvard Business Review (July-August, 1971) pp. 45-74
Cleland, D. I. And W. R. King, “Organizing for Long-Range Planning,” Business Horizons
(August, 1974) pp. 25-32
Delbecq, A.C., A. H. Van de Ven and D. H. Gustafson, Group Techniques for Program Planning:
A Guide to Nominal Group and Delphi Processes, Scott, Foresman, and Co. (1975)
Drandell, M., “A Composite Forecasting Methodology for Manpower Planning Utilizing
Objective and Subjective Criteria, Academy of Management Journal, Vol. 18, No. 3 (September,
1975) pp. 510-519
Janis, I. L., Victims of Group Think, Boston: Houghton Mifflin (1972)
Maier, N. R. F., Problem Solving Discussions and Conferences: Leadership Methods and Skills,
McGraw Hill (1963).
Nutt, P. C., “The Merits of Using Experts or Consumers as Members of Planning Groups: A
Field Experiment in Health Planning,” Academy of Management Journal, vol. 19, No. 3
(September, 1976) pp. 379-394
Pfaffenberger, R. C. and Patterson, J. H., Statistical Methods for Business and Economics,
Richard D. Irwin (1977)
Rumelt, R. P., “Strategy Evaluation: The State of the Art and Future Directions,” Business
Policy and Planning State of the Art Workshop, Pittsburgh (May, 1977)
Sackman, H., Delphi Critique: Expert Opinion Forecasting and Group Process, Lexington, Mass:
Health Lexington Books (1975).
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