One of the great puzzles in the business world (and indeed in other walks of life such as politics) is explaining why smart people often make dumb decisions. For example, Blockbuster's executives had the opportunity to buy Netflix for $50 million in 2000, but they turned it down – and Netflix went on to wipe Blockbuster out entirely. To make sense of decisions like these, we not only need to understand the strategic context in which they were made, but we also need to consider the psychology and group dynamics of the decision makers. Although there are many benefits to getting multiple people involved in decision making, it turns out that teams are often remarkably dysfunctional.

To make better decisions as a manager, you first need to understand established techniques that provide systematic insight into the issue at hand. For the most part, these are highly rational techniques. The first is to decide if an investment or a choice makes financial sense on the basis of current information (#38). Then you need to take into account multiple quantitative and qualitative factors (#39), and a broader range of qualitative aspects such as opportunities, risks, reactions, and ethics (#40). You need to consider the downsides as well, in terms of understanding what could potentially go wrong (#41) and prioritizing risks by impact and probability of occurrence (#42).

But it is also important to be conscious of the limitations of all these techniques. In particular, you need to be aware of your own cognitive biases and flaws, so that you can avoid making the types of blunders that sometimes derail the smartest executive teams. There has been an enormous amount of research on this issue, and we suggest one framework called avoiding cognitive biases in decision making (#43) to acclimatize you to it. We also provide links to other sources of advice on this at the end of the chapter.

Needless to say, the best decision makers are adept at combining the rational and more intuition-based elements of the process: They gather all the available data to arrive at a provisional outcome, but then they allow their experience and intuition to guide them to their final decision. Amazon.com, for example, is well-known for using data to inform its decision making but also for occasionally making enormous leap-of-faith decisions, such as launching the Kindle or moving into the movie-making business.

38. Decide Whether a Decision Makes Financial Sense (Net Present Value Analysis)

The baseline for any business decision is some sort of financial projection – will this project make money? Such analyses become complex very quickly, and this is not the place to get into the details of financial analysis. But it is important to understand the basic principles and, in particular, the notion of net present value (NPV) that is central to most financial projections and spreadsheet analyses.

In crude terms, every business decision involves spending money to make money. But the timings of these cash flows – money out and money in – are vitally important because a dollar today is more valuable than a dollar tomorrow. So, how do we quantify this?

This is where NPV analysis comes in – it is a way of calculating the value of a future payment as if it were made today by applying a “discount rate.” For example, $100 paid to you one year from now with a discount rate of 10% would have an NPV of $90.

NPV analysis involves estimating all the future cash flows (in and out) for a specific project under consideration and then discounting all these cash flows back to the present to figure out how profitable the project is.

For example, let's say a manager needs to decide whether to refurbish his factory's machines or buy new ones. Refurbishing (for $100,000) costs less than buying new machines (for $200,000), but buying new delivers a higher stream of cash flow. Thus, over a five-year period, we compare as follows:

You can see that the initial investment is paid back more quickly in the refurbish scenario – two years, rather than three. Some people like to think in these terms, but it is not advisable because it fails to account for the longer-term benefits that might accrue from the investment.

NPV analysis applies a discount rate to each of these cash flows. If you assume a discount rate of 10%, you get the results below. It suggests the manager should buy new machines because the investment delivers, over a five-year period, a higher net present value.

This basic calculation can be made a lot more sophisticated if you wish – you can create scenarios with different discount rates, and you can look at longer time periods. A variant of this analysis is called internal rate of return, which is a way of determining the discount rate for a given project assuming the NPV is set to zero. However, such details are beyond the scope of this book. We provide a reference below if you want to know more about this topic.

39. Choose Between Options and Considering Multiple Factors (Decision Matrix Analysis)

Few decisions in business come down to just a single factor, such as cost. For example, if you choose a supplier purely because they offer the lowest price, you can end up with poor-quality goods, or you may find the goods are produced in an unethical way, such as using child labor.

So you need to take many different factors into account in your decision making, and this can feel like comparing apples to oranges. How do you do this in a rigorous way that you can justify to people who may later challenge your decision? This is where decision matrix analysis can help.

1. List the factors you want to use to make your decision as column headings in a table, similar to Figure 7.1.

   

2. Enter a row on the table for numerical weightings that you'll apply to each factor. These show its relative importance, measured on a scale of, say, 1 to 5. If one of your factors is relatively unimportant, give it a 1; if it's highly important, give it a 5. You can see an example in Figure 7.2: Cost and quality are highly important in the final decision, but the supplier's location and delivery reliability don't matter as much – perhaps there are plenty of quick alternatives if delivery fails.

   

3. Enter table rows underneath for each of the options you're evaluating. For each row, score the option by each factor on a scale of 0 to 5, where 0 means that the option is very poor and 5 means that it's very good. (Ignore weightings at this stage.) See Figure 7.3.

   

4. Finally, multiply each of these scores by the weighting for each factor, and total each row. This shows how well each option scores relative to the other options, and answers the question of which option is best for you. You can see this in Figure 7.4. (Here, the row values shown are the scores from step 3 multiplied by the weighting from step 2. In this example, supplier 4 is the best option because it offers the best mix of quality, location, and reliability of delivery.)

   

40. Consider Many Factors, Such as Opportunities, Risks, Reactions, and Ethics in Decision Making (ORAPAPA)

NPV and decision matrix analyses help you choose between options in quite a robust way. However, there are many reasons why they don't give you the full picture, so it is always important to sense-check your decision. This is particularly important given the cognitive biases and flawed group dynamics that often plague decision making (as we discuss in #43). Although you can never entirely prevent flawed thinking, you can at least become more conscious of the potential risks you are facing.

This is where the ORAPAPA checklist comes in handy as a list of factors to consider when you're evaluating a significant decision. It's particularly useful for teams, because it allows people to step back from entrenched positions they may naturally adopt and helps them look at the decision using a variety of perspectives that they may not intuitively use.

ORAPAPA stands for opportunities, risks, alternatives and improvements, past experience, analysis, people, and alignment and ethics. Take a course of action you're looking at, and sense-check it using each heading:

• Opportunities – By brainstorming the opportunities the decision opens up, the team can bring the positives out into the open. This ensures that the optimists on your team are fairly heard and that their opinions are respected.
• Risks – With all of the enthusiasm and passion that goes into making a case for change, it's easy to underplay the risks that can go along with a decision. So this heading gives your team permission to explore the risks thoroughly without being labeled “naysayers.” Considering risk properly is a fundamentally important part of making mature, wise decisions as we discuss in more depth in #41.
• Alternatives and improvements – It takes a lot of effort to reach agreement on a particular option. Even then, there may be problems with that option, including foreseeable negative consequences and risks that you need to address. So are there further alternatives you should consider? And could you improve the idea still further?
• Past experience –Your organization may have tried something similar before. Situations change, and what may not have worked in the past may work now, but it's foolish not to learn from past experience. So spend time thinking about similar situations in the past and how you can learn from them.
• Analysis – Check the numbers used to support your decision, and make sure that these are robust. Ensure that sufficient analysis has been done, and double-check any explicit or unknowing assumptions you may have made. Then ask yourself whether your decision is aligned with general trends in the market, and sense-check your decision-making process to ensure that it hasn't been affected by issues of poor group dynamics (see #37) or psychological bias (see #43).
• People – Think about how your stakeholders and the wider community will react to the decision based on their limited knowledge (remember, most people will have no appetite for understanding the detailed pros and cons of your decision – they will use their intuition or “gut” to tell them whether they agree with it). This step prompts you to ensure that you've thought about stakeholder management and stakeholder communication – see Chapter 18 for more on this.
• Alignment and ethics – Finally, you need to confirm that the decision aligns with your organization's vision and mission and that it is ethical. This is tricky if you stand to make a lot of money, or if you're heavily emotionally invested because of all the work you've done on the decision. However, as we've seen in all sorts of recent, high-profile cases, ethical lapses can be disastrous for organizations and for the individuals involved.

41. Analyze Systematically What Could Go Wrong (Risk Analysis and Risk Management)

As we saw in #40, risk is something we always need to consider when we're making a significant decision. Almost all business decisions involve risk of some kind and the possibility of damage being done to the organization.

The trick is not to avoid risk altogether but rather to identify and understand the risks you're engaging with and manage them in an appropriate, pragmatic way. Openness to a balanced risk analysis is, therefore, a key differentiator between being seen as an unreliable “loose cannon” or a trustworthy and wise leader.

There are two parts to risk – the scale of a possible negative consequence (often measured as a cost) and the likelihood of it happening (measured as a probability). The first part of risk analysis is to identify possible threats. For big decisions, it's useful to gather together an experienced, multidisciplinary team to provide a range of insights into the range of threats you might face.

In a stable, established industry, you may be able to draw on established risk management protocols or checklists to give your team a good starting point for assessing risk. But it's still useful to supplement these with a mixture of failure mode and effects analysis (FMEA) (see the URL below), a cause and effect analysis-like approach (#34), and brainstorming (#48) to try to spot other risks that are specific to your situation.

If you're in a less established business setting, you'll need to use a range of approaches and develop your own framework. The range of risk areas is likely to be much broader – for example, including human, operational, reputational, procedural, financial, technical, natural, and political risks – see the URL for this below.

The next step is to estimate the risk. For each risk factor, estimate the cost if it occurs (usually relatively straightforward) and the probability of it occurring (typically much harder). By multiplying cost and probability together, you can get a value for each risk, and this can help you prioritize. (See #42 for more on this.)

How can you manage the risks you've identified? Review the most important ones, and think about how you can avoid them, mitigate them to a reasonable level, or transfer them – for example, by paying for insurance or hedging a currency transaction. Ultimately, there will be some risks that you need to accept, and you'll need to create contingency plans to manage them if they occur. (For more on risk management, follow the link below.)

42. Prioritize Risks by Impact and Probability of Occurrence (The Risk Impact/Probability Chart)

Risk analysis is important, but you can quickly end up with a worryingly long list of possible risks. It can be intensely time-consuming to address all of them, and this is where the risk impact/probability chart comes in (see Figure 7.5) as a way of identifying the ones you should focus most of your effort on.

An approach that has been in general use for several decades, the chart suggests four generic categories of risks:

• Low impact/low probability risks – These risks are unlikely to materialize, and it doesn't matter much if they do. You can often ignore them and just cope with negative consequences as they appear.
• Low impact/high probability risks – You can cope with these if they occur, but you should take sensible steps to stop them from happening because they can slow you down.
• High impact/low probability – These are unlikely to occur but can cause big problems if they do. Do what you sensibly can to reduce the impact if they transpire, and make sure you have appropriate contingency plans to deal with them. Pay particular attention to risks involving people's lives or the failure of your organization; for everyone's sake, you need to protect against these situations carefully.
• High impact/high probability – These risks are of key importance, and you need to focus large amounts of your time and resources on managing them.

43. Avoid Psychological Bias in Decision Making

Imagine you're researching a potential product. You think the market is growing, and as part of your research you find information that supports this belief. As a result, you launch the product, backed by a major marketing campaign, but the product fails. The market hasn't expanded, so there are fewer customers than you expected. You can't sell enough of your products to cover their costs, and you end up with a loss.

In this scenario, your decision was affected by confirmation bias. You interpreted market information in a way that confirmed your preconceptions – instead of seeing it objectively – and you made the wrong decision as a result.

Confirmation bias is one of many psychological biases to which we're all susceptible when we make decisions. There is now an enormous body of thinking about this phenomenon, building on the work of the Nobel Prize – winning psychologist Daniel Kahneman and his late collaborator Amos Tversky.

Psychological bias – also known as cognitive bias – is the tendency to make decisions or take actions that go against systematic logic. For example, you might subconsciously make selective use of data, or you might feel pressured to make a decision by powerful colleagues. Psychological bias is the opposite of clear, measured judgment. It can lead to missed opportunities and poor decision making. Here are five common psychological biases that can lead us to make poor business decisions.

Other Useful Decision-Making Techniques

In addition to the tools recommended in our survey, we believe that you need to use a robust process to make good decisions, and you need to conclude this with a solid go/no-go decision. Find out more about these at http://mnd.tools/c7c.