Home
 
Information
Sources

 
Training &
Seminars

 
About
Btt

 


 

 

Page 3 of 8

Risk Management: 
A practical toolkit for identifying, analysing and coping with Project Risk
 

An example...

Plan [IF Euro is used in UK] 99%


The above is an example where the risk is controlled by making the specification totally dependent on the IF condition. There is no risk that anyone will plan to achieve 99% if the condition is false. However, they are warned to plan to achieve 99% should the condition turn true.

Note, you can also use IF qualifiers to constrain the use of a strategy (a means for achieving a goal). This reduces the risk that an expensive strategy is applied under inappropriate conditions.

Strategy99 [IF hunger famine in a country, IF road and rail transport unavailable] Aerial Supply of Food.
Principle 2. Maximize profit, not minimize risk

Focus on achieving the maximum benefits within budget and time-scales rather than on attempting to eliminate all risk.

Elimination of all risk is not practical, not necessary and, not even desirable.

All risk has to be controlled and balanced against the potential benefits. In some cases, it is appropriate to decide to use (and manage) a strategy with higher benefits and higher risks. I use Impact Estimation (IE) to help me assess the set of strategies I need to ensure I meet the required objectives. My focus is always on achieving the objectives in spite of the risks.

Outline Description of Impact Estimation (IE)

The basic IE idea is simple: estimate quantitatively how much your design ideas impact all critical requirements. This is achieved by completing an IE table. The left-hand column of the table should contain the objectives and, across the top of the table should be the proposed strategies. For the objectives, assuming you have expressed them using Planguage, it is a question of listing down all the quality and resource attributes you wish to consider. You need next to decide on a future date you want to use. This should be a system ‘milestone’; a date for which you have specified Must and Plan levels. Then, against each attribute, you state the current level and the Plan level for your chosen date. (If you are especially risk averse you would use the Must level!) For the strategies, you simply list them across the top of the IE table.

You then fill in the table, for each cell you answer the question, ‘How does this strategy move the attribute from its current level towards the Plan level?’ First you state the actual value you would expect and then you convert this into a percentage of the amount of required change.

For example, Training Time for Task A is currently 15 minutes and you require it to be 10 minutes within six months. You estimate Strategy B will reduce Training Time for Task A to 12 minutes. In other words, Strategy B will get you 60% of the way to meeting your objective. See Table 1.

TABLE 1

 

Strategy B

Real Impact %Impact
Training Time
Past = 15 minutes in June 1998
Plan = 10 minutes by end Dec. 1998


12 minutes
 

60%

Resource = Development Budget
Plan = $2,000 up to end Dec. 1998

$1,000

50%

Further improvements to specifying the impacts
There are a number of improvements to this basic idea, which make it more communicative and credible. Here is a brief summary of them:

Uncertainty of Impact: you can specify a range of values rather than a single value.

Evidence for Impact Assertion: you can state the basis for making your estimate.

For example: "Strategy B was used for 5 projects last year in our company, and the percentage improvement for Training Times was always 60% to 80%".

Source of Evidence for Impact Assertion: Of course, some skeptic might like to check your assertion and evidence out, so you should give them a source reference, e.g. "Company Research Report ABR-017, pages 23-24."

Credibility Rating of the Impact Assertion: We have found it very useful to establish a numeric 'credibility' for an estimate, based on the credibility of the evidence and the source. We use a scale of 0.0 to 1.0 (because it can then be used later to modify estimates in a conservative direction). See Table 2.

TABLE 2

EXPLICIT RISK SPECIFICATION

0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0


wild guess, no credibility
we know it has been done somewhere
we have one measurement somewhere
there are several measurements in the estimated range
the measurements are relevant to our case
the method of measurement is considered reliable
we have used the method in-house
we have reliable measurements in-house
reliable in-house measurements correlate to independent external measurements
we have used the idea on this project and measured it
perfect credibility, we have rock solid, contract-guaranteed, long-term, credible experience with this idea
on this project and, the results are unlikely to disappear

Further Analysis of the IE data

Once you have completed filling in all the impacts, there are a number of calculations, using the percentage impact estimates (%Impact), that help you understand the risks involved with your proposed solution.

more...

 

 © Tom@Gilb.com 2005 
 
Back to: Projects Implementation      Back (previous): Page 2 of 8     Next: Page 4 of 8
 

 

Copyright © Biness Transition Technologies Ltd 2004.  A

ll Rights Copyright © Business Transition Technologies Ltd 2006.  All Rights Reserved.