Many sales professionals will shy away from the subject of risk, preferring to play down or deliberately ignore the inherent risks in their proposals. Good sales professionals will realise that risk can be turned around to become a massive competitive differentiator and the way that risk is dealt with can be the difference between winning and losing a deal. So how can we handle such a delicate subject so that it is turned to our advantage?
Quantifying cost risks as a route to the lowest price
If we can accurately identify the cost risk in the deal, we will be well placed to offer the lowest competitive price and hence be in a strong position to ultimately win the deal. Unfortunately there are significant challenges in quantifying the risks using traditional risk methods, as the numbers are little more than guesswork with little or no consistent rationale behind them. Few potential clients are going to buy into this approach and it may come over as simply a way of inflating the price.
The ABCD Quality Based Costing (QBC) technique is a way of modelling uncertainty in a way that ensures that the best data available is used and fully justified. It essentially works by acknowledging the inevitable quality variations in the estimates and underpins all estimates with their underlying assumptions to explain these quality variations.
The QBC technique breaks down the overall costs into Bricks and then breaks down each Brick into its “quality components” based on the confidence in the data available. The assumptions captured explain what is happening between each transition in the Brick (eg what assumption needs to happen in order that you can keep to an A+B estimate and not need the C). The key factor here is that the ratings of the assumptions must be consistent with the estimate breakdown and the interview often results in challenges to the estimates and/or assumptions to make them consistent. One significant benefit is that inappropriate contingency will be stripped out and required contingency will be maintained or added in.
Monte Carlo simulations are then run to statistically add the Brick estimates together. The resulting probability distributions can be interpreted to make crucial decisions relating to budgeting, pricing and contingency.
Obviously a commercial decision might be agreed to price the deal at a loss but a typical starting point would be to take the 90% cost and add a “reasonable” margin. The next step would be to look at all the contingencies that have been added to cover 3rd party commitments. Potentially these can all be removed, the model re-run and the underlying assumptions highlighted and quantified explicitly so the client has full visibility. Subsequent negotiations may result in the client asking you to take on these risks but then you will be getting paid appropriately to do so. In this way, you will be able to offer the lowest price (fixed if appropriate) and still cover yourself for the explicit risky assumptions that you have identified. Ultimately these assumptions can be written into the contract and individually priced so that, if not managed, they will trigger additional payments.
Guaranteeing delivery
As important as cost/price and possibly more important to the client is their confidence in your ability to deliver to agreed timescales. The client is undertaking the project to gain tangible and/or intangible benefits. It is highly likely that any delays to delivery times will be eating away into these benefits, and delaying them at the very least, so anything that you do to show that you stand a higher chance of delivering on time than your competitors could be crucial in securing the deal.
Using the ABCD QBC approach, the timescale risk can be accurately quantified in a similar way to the cost risk. The main difference here is that the timescale “Bricks” will be the activities that lie along the critical path (ie the longest route through the project plan). Be aware that at the deal stage the critical path may not be obvious and there may be multiple potential critical paths that are possible due to the statistical nature of the model. The solution here is to model all potential critical paths to see which is actually the longest – there should not be too many!
The initial timescale assessment should be done as early in the proposal stage as is practical (ie as soon as outline plans are available – the model can be updated and run again relatively easily if the plans change). This will yield a probability distribution that will allow you to read off the percentage probability of achieving any given target date. It is not unusual to discover, at this stage, that the target date has a relatively low probability of being achieved. Increasing the probability is a matter of managing (or showing how to manage) the underlying assumptions. As in the cost analysis above, you can legitimately “discount” the delays that would be due to the client and third parties. You can then show a profile that shows a high probability of delivery if the client and third parties meet their commitments. It may also be appropriate to show different scenarios based on whether these risks are managed effectively or not.
Sometimes the initial assessment shows that the target date has a “0%” chance of being achieved. This means that the delivery target is impossible with the current approach and will require a differently structured plan i.e. more activities will need to be planned in parallel.
It is important to note that the estimates you are putting into this assessment are all yours as there is unlikely to be any client (or third party) input at the proposal stage. This should not be a problem as it demonstrates a high degree of understanding and transparency and may open up a productive dialogue with the client. The analysis also shows the client how the timescale risk can be systematically reduced by managing the identified assumptions. It should be made clear that the analysis will be re-done, jointly, following contract reward.
As in the cost analysis, the assumptions will uncover opportunities as well as risks so you may even be able to identify how you could deliver early. The competition is unlikely to have thought of that one!
Shadowing the competition’s risks
It is very common for clients to ask suppliers to identify the risks as part of the proposal. Very often this results in suppliers providing a highly sanitised risk register that only expose the risks that the supplier is comfortable to discuss. Intelligent clients realise what is going on and may penalise suppliers for not being open or not understanding their business issues.
Further, you may be aware of risks that you are well positioned to manage but you suspect that the competition is not. It is then difficult for you to highlight these risks, using traditional risk management methods, without coming over as overtly negative.
Using ABCD Assumption Analysis, shadowing the competition’s risks becomes a lot easier to do as you are focussing on the positive assumptions rather than the negative risks.
All the assumptions that must happen in order to deliver the clients objectives should be listed. The assumptions should be rated honestly from your perspective and any which are “at risk” should have substantive mitigation plans. For assumptions that you are confident that you have edge over the competition, stress your strengths clearly and leave it at that!
You will probably create a checklist against which the competitions’ risks will be compared and inevitably there will be “gaps” that will seed doubt in the client’s mind that the competition is either not being completely honest or do not understand the problems that the proposal is supposed to address. Either way, you win.
There is obviously additional cost in using the techniques described here but the ROI should be very high. Firstly, you would only use the approaches on your most strategically important deals and secondly, remember the difference in return between coming first and second!