In a good project underspends are just as bad as overspends. I look on this scenario from the perspective that if my staff managed to calculate the budget that inefficiently in all likelihood the actual deployment was flawed as well - in ways that I can't yet know. The big issue is: How good are the planning and budgeting skills? While I've used these in the same sentence, and the benchmarking model below uses budgeting as its template, planning skills are (i) a separate and just as important issue as budgeting and (ii) the IC model below applies in all its principles, to planning skills as well as budgeting skills. The measurement parameters will be slightly different.
In any benchmarking exercise we seek to give managers an iterative process. How close the management come to the benchmark and in what manner are key areas of interest. Typically we would want to employ managers that are already excellent practitioners of both. The reality is that these are fluid issues. So, I will take them from the perspective of a clean start. Readers may assume for their own financial firms a start point somewhere along the line. Wherever the managers start, its to be expected that expenditure on planning, budgeting and training will deliver results that improve performance which asymptotically approaches some given benchmark. If the performance of a manager at the start is low, that is, budget planning versus reality has large differences, then more money will need to be spent on oversight activities. What is important here is that if you don't let the manager learn and get better at his craft in your environment you won't reap the rewards.
However, it is clearly unacceptable to have these people making critical mistakes. So senior managers need to understand how to juggle these issues successfully. Let us presume that we take one performance measure - budgeting skills. The manager will have a set of skills in this area from historical projects which can be tested and analysed. For this purpose however we will assume no previous knowledge. The benchmark may be, often is, that the manager should be able to budget to within a 95% confidence interval.
This means two things. First that the manager must be able to budget a project and have the actual measured spend be within 95% plus or minus an acceptable margin of error. Second, the manager should be able to reproduce this performance with consistency again in the 95% confidence interval.
This methodology acceptably deals with the most common mistakes of middle and junior managers, that of ‘contingency building'. The feeling is that all projects must come in under budget and that overspends are bad. This is simply not reasonable in financial technology deployments. The issue is actually how consistently can a manager calculate the various variables and create a budget that is a reasonably accurate estimate. This, when successfully delivered, builds trust between senior and middle/junior managers. This has far-reaching consequences. Those project managers that can sow reliability in budgeting will naturally be given the more sensitive and critical projects. They are also more likely to be given the larger-cost projects where a percentage point overrun could mean millions of dollars. Training is of course the key, as with so many things. The first represents what would be expected in a perfect world. The second represents the real-world situation. Each improvement is associated with a plateau.
The plateaux represent a consolidation period where skills learnt in the previous cycle are embedded in the manager and training takes place to address those areas that need improvement. shows how the plateaux can be deconstructed into a simple cycle. For technology management projects, financial firms need to view the delivery of value holistically. This first element is looking at how well the firm performs over time. One of the interesting things about this type and level of benchmarking methodology is that it is very rare for the top levels of management to be subject to it. This is a C-level issue and the benchmark system if implemented correctly starts with C-level staff being assessed as to their ability to improve the cycle. Effectively this means that in a more efficient organisation, the number of plateaux in and the distance between them are minimised by effective training and analysis. The net result is the business becomes much more effective than its competitors at delivering value to the business when measured as a function of efficient planning. I say this because at middle and junior management levels, this type of benchmarking is more common. These levels expect to be measured and expect to go through a ‘professional development' cycle. C-level staff where Ap is a measure of the assimilation plateau, Vc is the value delivery curve and n represents the number of such cycles lying between the start of the assessment period and the achievement of the 95% confidence benchmark.
There are different features of this model. First, it gives numeric analytical ability to a management function. Second, it allows for a number of sublevels of possibility for senior managers. Here are some examples:
1. The larger the number of Ap events, the smaller the time horizon of the individual technology manager. In other words, their attention span is short and they need multiple small events to achieve a higher level of skill. This may be a retention issue.
2. If the first derivative of the Ap or Vc curve is taken, that is if we measure the rate of change of curvature, this represents the rate at which training is effectively being absorbed and translated into value.
3. IC itself is an effective measure of performance improvement indicating how quickly a 95% confidence can be assigned to a project manager's budgeting or planning skills.
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