By Steven Finlay (auth.)
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Extra info for Credit Scoring, Response Modeling, and Insurance Rating: A Practical Guide to Forecasting Consumer Behavior
All projects are subject to a degree of uncertainty and things don’t always go to plan. The way the project manager deals with unforeseen events is to trade-off objectives against each other (Mantel et al. 2007, pp. 6–7). If the project slips behind schedule because data analysis is more complex than originally envisaged, then the project could be brought back on track by obtaining more analyst resource (at more cost). If this is not possible then a decision may be made to reduce the number of things that are delivered, or settle for something that works, but is sub-optimal.
If the quality of the deliverables has been deliberately sacriﬁced to obtain a quick win, then it is very important that this decision is approved by senior management and documented for prosperity. Otherwise, it can leave the project team exposed to accusations of cutting corners and shoddy work at a later date. On more than one occasion I have witnessed very capable and highly skilled people being accused of incompetence and blamed for delivering sub-standard solutions by people who only became involved in the project towards its conclusion, and were unaware of the quality/time/cost trade-off decisions that were made or the reasons for them.
Sometimes there can be pressure to just “get on with it” and start gathering and analysing data as soon as possible. Project planning is viewed as a form of procrastination, delaying the start of the real work that needs to be done. This may be the case, but the old adage “more haste, less speed” generally holds true. As a rule, making changes towards the end of a project is much more time consuming (and hence more costly) than making the same change near the start. This is because of the knock on effects each change has on subsequent activities.