Risk Management

[article]
A practical toolkit for identifying, analyzing, and coping with project risks
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At least, with the use of an IE table there is a chance of
expressing and comparing the risk involved in following the differing strategies.

Principle 4. Design in redundancy
When planning and implementing projects, conscious backup redundancy for outmaneuvering risks is a necessary cost.

Under Principle 3, we have discussed finding new strategies. Principle 4, takes this idea a step further. Actively look for strategies that provide backup. An extreme example of this practice is NASA's use of backup computer systems for manned space missions.

Principle 5. Monitor reality
Early, frequent and measurable feedback from reality must be planned into your development and maintenance processes to identify and assess risks before they become dangerous.

I expect the IE information only be used as an initial, rough indicator to help designers spot potential problems or select strategies. Any real estimation of the impact of many strategies needs to be made by real tests (Ideally, by measuring the results of early evolutionary steps in the field). Evolutionary Delivery (Evo) is the method to use to achieve this (See next Principal).

Principle 6. Reduce risk exposure
The total level of risk exposure at any one time should be consciously reduced to between 2% and 5% of total budget.

IE can also be used to support Evolutionary Delivery (Evo) as a budgeting and feedback mechanism during project building and installation of partial deliveries [GILB98, MAY96].

The Evolutionary Delivery (Evo) method typically means that live systems are delivered step by step to user communities for trial often (e.g. weekly) and early (e.g. 2 nd week of project).

One of the major objectives of Evo is to reduce and control risk of deviation from plans. This is achieved by:

  • getting realistic feedback after small investments
  • allowing for change in requirements and designs as we learn during the project
  • investing minimum amounts at any one time (2% to 5% of project time or money) so that total loss is limited if a delivery step totally fails.

IE is of use in helping to plan the sequencing of Evo steps. IE tables also provide a suitable format for presenting the results of Evo steps. See Table 5.

 TABLE 5

Step->

Attribute

STEP1

plan

%

actual

%

Deviation

%

STEP2 to STEP20

plan

plan
cumulated
to here

STEP21 [CA,NV,WA] plan

plan
cumulated
to Here

STEP22 [all others]

plan

plan
cumulated to here

QUAL-1

5

3

-2

40

43

40

83

-20

63

QUAL-2

10

12

+2

50

62

30

2

60

152

QUAL-3

20

13

-7

20

33

20

53

30

83

COST-A

1

3

+2

25

28

10

38

20

58

COST-B

4

6

+2

38

44

0

44

5

49

Table 5 is a hypothetical example of how an evolutionary project can be planned and controlled and risks understood. The 'deviation' between what you planned and what you actually measured in practice is a good indicator of risk. The larger the deviation, the less you were able to correctly predict about even a small step. Consequently there is a direct measure of areas of risk in the 'deviation' numbers.

The beauty of this, compared to conventional risk estimation methods [HALL98] is that it:

  • is based on real systems and real users (not estimates and speculation before practical experience)
  • is early in the investment process
  • is based on the results of small system increments, and the cause of the risk is easier to spot, and perhaps to eliminate, or to modify, so as to avoid the risk.

Evolutionary Project management does not ask what the risks might be. It asks what risks have shown up

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