6 Great Tips to Improve Your Leadership & Decision Making

Just finished a podcast from the Centre for Creative Leadership on decision making myths, discussion how business executives and leaders can improve their decision making skills. They start off examining the paradox of leadership, and how ego and confidence can be great leadership qualities, yet also handicap team decision-making processes.

The problem seems to focus on being able to exhibit decisive confidence when it’s necessary, yet still encourage debate and ideas that challenge the status quo. Decision-making research has shown that the best strategic decisions don’t come from teams that go for the easy consensus, but from consensus found through vigorous debate. Creating this environment takes sharp communication skills.

Here are the 6 tips they offer (paraphrased):

1.)  Try it again – just because something didn’t work before, don’t rule it out. Times change, adapt with them;
2.)  Slow down and ask questions – hasty decisions often miss the knowledge that time unveils;
3.)  Operate at the edge of chaos – Show confidence you’re open to debate, disruptive ideas;
4.)  Ask & listen – when ideas start coming, ask questions and listen. Confident leaders go outside their inner circle for ideas & input knowing this isn’t a reflection on their abilities;
5.)  Get some help – as well as asking for input, confident leaders know their strengths and weaknesses and when to get outside help to see things from a different perspective; and,
6.)  Let the ego go – delegate effectively, and build a strong and effective team by letting go of control at the right times.

Risk Assessments Are Decisions Too

Risk is a concept that everyone understands and almost no one evaluates very well. Risk is a function of both the likelihood that something will happen and the consequences that result if it does. When evaluating risks we always seem to be more focused on one or the other.

For example, driving without your seatbelt entails a risk. Those who do usually focus on the likelihood of getting into an accident: “I’m just going around the corner”, rather than the consequence, which could be serious injury or death. Conversely, the decision to buy a lottery ticket is usually based on the consequence, “I could be a millionaire!”, rather than the likelihood of it happening, which is extremely low.

Correctly evaluating risk requires an honest consideration of both likelihood  and consequence. Statisticians, mathematicians and actuaries examine joint probabilities to evaluate risk. Simply put, they multiply the probabilities together to evaluate the possible outcomes. So if you are faced with a financial investment choice that has a 25% chance of paying $10,000 or a 10% chance of paying $25,000, your financial risk is the same (because 0.25 x 10,000 and 0.10 x 2,500 both equal 2500, your theoretical pay-off). Simple.

Things get complicated because there is often uncertainty (or in a mathematical sense, distributions) associated with both the likelihoods  and consequences, and complex decisions often involve a cascade of nested or otherwise related risk assessments.

Keeping the math straight is the job of decision models, and making it transparent is the job of (good) modelers.

Who built that bridge you're standing on?

I’ve been listening to an interview with Tom Davenport from the recent The Premier Business Leadership Series in Las Vegas, and he raised an interesting point regarding the role decision models played in the recent meltdown in the financial sectors.

Models provide a bridge between large volumes of complex data, and the judgment of executives who make major decisions based on the data. Many have been blaming the models for the bad decisions that led to the collapse.

Tom Davenport pointed out that the models weren’t always at fault. He instead believes that the problem was the disconnect between the executives using the models, and the underlying model assumptions. He states “analysts need to be much more transparent about the assumptions behind the models…[and] if they’re not providing that, [executives] need to really push back…”

The message here is that models are only as good as the assumptions that they’re based on, and assumptions should be scrutinized as closely as the outputs. Ask questions, challenge how these bridges are built, and balance it all with your own good intuition for a better and more profitable decision-making process.

Science 101 for Business Leaders

I can say this because I was trained as one: scientists are geeks. They are lousy team players and most have as much business sense as a test tube. But they have figured out something that businesses can benefit from. It’s widely misunderstood but extremely powerful: the scientific method.

photo credit: blondyimp

Science is all about testing hypotheses: statements about how we believe the world works. But rather than conducting experiments to support their hypotheses, scientists actually spend all of their time trying to prove that they’re wrong. And it’s actually very difficult to design experiments capable of revealing critical flaws.

Knowledge is simply what’s left when we run out of ways to disprove our ideas.

What can businesses learn from the scientific method? Finding evidence to support our intuition can be easy but is not very useful. Instead we should be listening to the nay-sayers, the contrarians, and uncovering every alternative and option.

Great ideas, processes and products are often not those we have reasons to love, but those we fail to have reasons to hate.

The Bull in the Boardroom

We’ve all been there. After a long and tiring round of discussion regarding a particularly complex situation, you’re close to agreement. Just as the debate is closing in on resolution, the door opens, and in charges the bull. Intuition.

Someone’s intuition disagrees with the emerging consensus, and it charges around being as agreeable as, well, a bull in a china shop.

So how do we tame this beast and, better yet, get it working for us? The strength of intuition is well known and respected in business, so we can’t exactly ask it to leave.

photo credit: Tambako the Jaguar

Nor would we want to. The intuitions of your decision team are far too valuable to ignore.

What’s missing in this situation is the right seat at the table. We need a framework within our decision-making process that can accommodate intuition, quantify it where possible, and consider it as we would any other data source we may have at our disposal.

Without a seat at the table, the bull of intuition will either disrupt consensus-building behind closed doors or, worse yet, reveal itself around the water cooler where the damage to your organization could be much greater.

Having intuition at the table will result in better decisions, as long as it’s participation is orderly – not charging down your business’ halls.

Balancing decisions

Seth Godin’s at it again, blogging about our favorite subject: decisions. His post Tuesday talked about the avalanche of data we now have at our disposal to assist in our decision-making, and how in many cases, because the data are counter-intuitive, they are ignored.

The real problem is the balance between intuition and data, and how they play in the process.

photo credit: Foxtongue

Data-heavy decisions become problematic when we infer relationships among sets of data that may not be there, or when we over-extrapolate current trends (as happened in the financial sector recently).

An over-reliance on intuition in a decision is just as bad. Bias traps aplenty lie in wait to lead decisions astray, or as Seth points out, good data simply get ignored because they are counter-intuitive.

What is the recipe for a great decision? One where data and intuition are considered appropriately within a clear decision-making process.

Balancing Intuition and Modeling

iTunes U is becoming a great resource for business-related information from some of the top business schools in the world. In this interview Dr. Stefan Scholtes of Cambridge University speaks to the issue of blending intuition and modeling in assessing financial risk, focusing on the breakdown that led to the recent financial crisis.

Make Better Decisions, Not More!

Just read Seth Godin’s post for today, about why it’s generally better to make more decisions, as opposed to making fewer. While I agree with Seth that just doing something can be better than nothing, I think that greasing the wheels of process (how we decide) will lead to better outcomes.

photo credit: Elsie esq.

Here’s what I mean. The people Seth is talking about – those deciding to do nothing (which as he points out, is a decision in itself), are likely having a hard time because they don’t have a clear thought process on how to make decisions. Good decisions happen like this:

Understanding – Step back two paces. What is it we’re trying to solve, fix, or make better? What are the outcomes we want?

Alternatives – what are the possible courses of actions we can take? Where will those alternatives take us?

Decide – After we better understand what we’re after, and have imagined alternative scenarios, picking a course of action (deciding) should be easier.

My main point is this: those locked in the quicksand of indecisiveness are typically there because they are overwhelmed by the complexity of their situation. So they do nothing. Take control of the process, and better decisions will happen.

Measuring Success with Bad Ideas

It might seem counter-intuitive, but one of the best measures of successful businesses is the number of bad ideas they generate.

Innovation is the lifeblood of any successful organization and ideas provide the raw material for innovation. But how businesses handle the bad ideas is as important as how they handle the good ones.

photo credit: oskay

Analysis and consensus are important when ideas are rejected or when unsuccessful projects are terminated.  Without them, rejected ideas and projects refuse to die, carried forward by inertia, sunk costs and a human need to avoid failure. This bleeds resources away from projects with better potential and, ultimately, impairs future innovation.

Generating a model that captures the essential structure of a proposed or existing project allows a team to focus on the process rather than on the players. This encourages creative thinking but provides a logical framework for evaluation.

The result is a stronger consensus among team members and better execution when the team does find the winning strategy.

4 Ways Bad Decisions Cost Real Money

Bad decisions can cost your company real money. Here are four ways it can happen:

1) Missing a better course of action. Did a decision result in only an adequate course of action, but miss the larger opportunity? At some point every decision requires you to choose a direction. The choices in front of you depend on how well you’ve explored the alternatives. Missing a better alternative because it’s un-intuitive can mean you’re leaving opportunity, and profits, unrealized.

2) Poor consensus. The test of a decision is how well related actions are executed. Starting down that road without full consensus from the implementation team will cause delays, misunderstanding, and other inefficiencies. Proper consensus (commitment + shared understanding) can greatly improve implementation results.

photo credit: Mark Strozier

3) Failure to implement. After slow implementations come failed ones. These are decisions that wither and die in execution, not because the decided course of action was wrong, but because  it was not structured well enough to be understood and committed to by the people getting the job done. Failed decisions are often expensive ones.

4.) Bad decisions can be habit-forming. Future decisions are built on past decisions. Poor decisions at the start of a project can lead to an expensive house of cards.

It’s clear that bad decisions can lose a business money (and customers) in many ways. What’s missing are better ways to measure these losses so efforts to improve decision-making can be bench-marked and validated.