So many projects that promise the earth end up costing too much, take too long to deliver or never quite do what they say – and analysis projects are just as prone to this as big infrastructure projects. However there are ways to mitigate the risk – you just need to look out for the warning signs, and if they start flashing get out quickly!
Warning sign 1 – “We’ll do it all for you”
This is a classic opening gambit in a sales pitch. Companies bringing in consultancies to do analysis projects typically do so because they have a resource and/or capability gap. A proposal that promises hands-off management is very attractive in these circumstances.
No business is the same – in terms of the data used, how the business operates, the decision making process etc. It is not credible that an external consultancy can absorb this understanding without committing sufficient time or resource to do this. It is those quotes that understate this work that should signal a red warning light. Ironically a proposal for work, which has significant time and effort allocated to knowledge gathering and understanding, should be seen as a positive not a negative!
Warning sign 2 – “Trust me I’m a big blue chip consultancy”
The logic is that risk is reduced by going for reputation and a track record of delivery with a big ticket consultancy. The argument is that while it may cost more, you know it will work so you save money in the long run. And look how glossy the promotional material is – and boy, do the employees sound credible!
Everything that we have said in regard to warning sign 1 applies even more to this situation. The day rate associated with the blue chips can make even the biggest company gulp and the natural inclination is to cut back on costs wherever possible – and the initial ‘knowledge and understanding’ work tends to be the area where the axe falls. Even if this part of the project survives, typically it is the handover or on-going support that is curtailed – often to recover an earlier cost over-run or simply because management priorities have changed as the project progresses.
The second risk area relates to how the blue chips operate. The calibre of the individuals is typically strong – quite simply you get what you pay for and they also have the reputations that attract the best. However with any company of significant size (and an audit heritage) the natural culture is one of conformity. Hence there are documentation and process standards – as a result the client often ends up drowning under a forest of paper, which needs costly time and resource to review and ensure that it reflects their requirements.
Finally businesses continuously evolve and change. For one-off analysis projects it isn’t such an issue but a significant number of projects hand over models or learnings that need to be updated to ensure they remain relevant. Certainly from a consultancy perspective these are far better solutions to sell into a company as there is the opportunity of future income. With a blue chip the ongoing cost becomes prohibitive for all but the largest organisations.
In summary, for many companies the glossy brochures are not necessarily the best solution. Technology is such that tools and techniques are no longer the preserve of the blue chips consultancies. Smaller suppliers can provide a more flexible and tailored approach that is relevant and can add more value to the client. They are also more likely to establish an ongoing relationship as they are not hamstrung by fixed processes and excessive overheads that result in inflated costs.
Warning sign 3 – “There will be no need for manual intervention”
This is the classic black box solution. The expectation is that there are standard approaches and all that is needed is to gather the right information from the client and then the commissioned model can be completed and handed over. The onus is then on the client to update it with the latest information and the model will continue to churn results as and when required.
The first risk is around the one size fits all mentality. I have yet to see a business where this works. Every company has its own quirks and foibles and ways of working. Typically you see IT projects where every effort is made to get the business to conform to the new system. Often this is the right thing to do and over time can work. In fact the risk is greater going the other way – adapting everything to the client results in the delivery of a bespoke solution that is difficult to maintain. In the field of analysis this argument is significantly weaker. Analysis is intended to add value to the business through insight – it is an agent of change and not a change in itself. Hence any deliverables or outputs need to be fit for purpose and usable by the client. In this situation the black box approach is unlikely to be the best solution.
The second area of concern is the assumption that the modelled outputs remain appropriate. Businesses constantly adjust, driven by changes in the markets that they compete in. The assumption that you can simply pass over a black box and say goodbye is flawed. There needs to be constant evaluation and verification to ensure that the model remains fit for purpose. There is no issue with passing this responsibility over to the client – similarly it may only need a review process on a quarterly or annual basis or when certain tolerances are breached. However I have seen many companies where key internal processes are based on a model or analysis that was completed many years ago and where there is nobody left who understands it. What they do know however is that the process notes say run the macro on a Tuesday and to type the prices that are generated into another system on Wednesday. If they do this they get a pay cheque at the end of the month.
The final risk in this area is the data itself. In my experience the maintenance and quality of data has deteriorated in companies. There are a number of reasons for this, but this is not the time or place to explore them. The consequence is that much greater care is needed to ensure the data, and assumptions that underpin the data, are valid. This applies to internal projects but even more so to external projects. This care is required not only as an initial input but also on an ongoing basis. It is very easy for data to subtly change (eg bringing in categories not previously reported) or data sources to change. This may be known – in which case the black box model will need to be updated – or not known – and so either the model will fall over, or start generating spurious results. The impact of this is cumulative over time and so the issue is not noticed initially. No matter the situation there is a need for transparency as to how a model or process works and an on-going process of review and evaluation to ensure it remains fit for purpose.
The clue is in the title – “buyer beware”. There is no approach that is always right but there are key principles that need to be considered when commissioning work.
- Solutions that work in isolation of the client usually end in tears. It is important to work with companies that have a good cultural fit or an approach that spends time understanding how your company works and ensuring that the project deliverables add the most value to you.
- Size isn’t everything – there a large number of smaller and niche operators who are able to match the big boys in terms of the quality of the output at a much lower cost and probably more importantly they are companies you can afford to establish an on-going relationship with.
- Transparency and ownership are increasingly important – if you do not have an explicit understanding or knowledge of the final model or basis of the analysis then you are at risk moving forward.
Awareness of these warning signs doesn’t mean you are guaranteed a positive outcome – but at least increase the chances of successful outcome!