The best thing you can do to manage risk?

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You ask: What's he best thing I can do to manage risk?

Answer:

Make time your friend. 

 

Insert time buffers in your schedule around every uncertain event, around milestones that are critical to success, and around major blocks of scope that determine whether project objectives will be met.

Time is your friend if it is allocated in your schedule to give you space to work, and rework, mitigations. Time is your friend if you have the space to accommodate the less optimum outcomes. 

But time is not your friend if you've not allowed for the consequence of coupling between risky outcomes, and have not provided a buffer space to work the work-arounds.

Beware of shift-right!

What's "shift right"? 

If a milestone success is determined by the likelihood of multiple independent outcomes finishing together, then the likelihood of the milestone finishing on-time is degraded by the product of their likelihoods. To restore the confidence in the milestone schedule, it has to be shifted to the right.

Example: Two independent outcomes of 80% confidence each result in a 64% confidence in their joint success

So, if you buffer that milestone in the first place, then the "shift right" is built-in from the beginning and is not a shock when it happens.

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Let's hear it for bureaucracy!

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If you can't trust your people

Or, you don't know your people well enough to trust them

And, you can't replace the former

Nor do you have time to get to know the latter .....

Then the management solution is simplicity itself:

Invent a bureaucracy and assign them to it!

Bureaucracy is the management alternative to trust. 

• Rules, regulations, and punishment do all the work. No fuss, no muss!
• Sometimes, incentives are useful, so don't leave them out.

Now admittedly, bureaucracy cuts against the flat, agile grain which is "the way to do it" for modern managers. 

But, beyond a point, flat is too flat, and agile is too agile.

Let's be realistic:

• Many can not handle complete freedom, 
• Have questionable judgement, 
• Are misaligned to strategic goals and imperatives, and 
• Generally spend time and money without regard to the fact that neither the time nor the money is theirs.

Bring on the bureaucrats!

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The only two things you need to know about statistics

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Number One: It's a bell, unless it's not
For nearly all of us when approaching something statistical, we imagine the bell-shape distribution right away. And, we know the average outcome is the value at the peak of the curve.

Why is it so useful that it's the default go-to?  

Because many, if not most, natural phenomenon with a bit of randomness tend to have a "central tendency" or preferred state of value. In the absence of influence, there is a tendency for random outcomes to cluster around the center, giving rise to the symmetry about the central value and the idea of "central tendency". 

To default to the bell-shape really isn't lazy thinking; in fact, it's a useful default when there is a paucity of data. 

In an earlier posting, I went at this a different way, linking to a paper on the seven dangers in averages. Perhaps that's worth a re-read.

Number Two: the 80/20 rule, etc.

When there's no average with symmetrical boundaries--in other words, no central tendency, we generally fall back to the 80/20 rule, to wit: 80% of the outcomes are a consequence of 20% of the driving events. 

The Pareto distribution, which gives rise to the 80/20 rule, and its close cousin, the Exponential distribution, are the mathematical underpinnings for understanding many project events for which there is no central tendency. (see photo display below) 

Jurgen Appelo, an agile business consultant, cites as example of the "not-a-bell-phenomenon" the nature of a customer requirement. His assertion: 

The assumption people make is that, when considering change requests or feature requests from customers, they can identify the “average” size of such requests, and calculate “standard” deviations to either side. It is an assumption (and mistake)...  Customer demand is, by nature, an non-linear thing. If you assume that customer demand has an average, based on a limited sample of earlier events, you will inevitably be surprised that some future requests are outside of your expected range

What's next to happen?
A lot of stuff that is important to the project manager are not repetitive events that cluster around an average. The question becomes: what's the most likely "next event"? Three distributions that address the "what's next" question are these:

• The Pareto histogram [commonly used for evaluating low frequency-high impact events in the context of many other small impact events], 
• The Exponential Distribution [commonly used for evaluating system device failure probabilities], and 
• The Poisson Distribution, commonly used for evaluating arrival rates, like arrival rate of new requirements

Two things are good enough
For project managers, central tendency is a 'good enough' working model  that simplifies a visualization of the project context.

Otherwise, fall back to the Pareto concept. It's good enough.

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Plausible denial

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What follows is an all-to-sad commentary on government. 

But what if "government" was "PMO" in this quotation? That would be really sad. 

Perhaps "lie" is too strong; perhaps 'self-delusional' or some other less in-your-face spin is more the case. But you get the point: the unvarnished truth is sometimes just too much for the moment. Time is necessary to find your way back on the center stripe. And to make time, some spin of the truth is required.

Perhaps; but plausible denial: that's running from responsibility. That can not be condoned.

“It is a truism that all governments lie: they lie to each other, they lie to their own people, they frequently lie to themselves. 

But a fundamental premise of functional government is that such deception .... must be an exception rather than a norm: to rule effectively, a government must be able to maintain at least a minimum level of credibility; by the same token, it must inevitably fail when it chooses to function on plausible deniability alone"

Daniel Allen Butler

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Two choices

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To a senior manager:
"What is the best way to manage a project?”
In response:
“You’ll find that there are always two possible decisions open to you,” the senior manager replied crisply. “Take the bolder one—it’s always best"

Daniel Allen Butler (paraphrased a bit)

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Perfect proposals (by Clayton)

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Do you read Mike Clayton? You probably should.

Here is his idea of the 12 points of a perfect proposal:

What are the elements of a perfect proposal? Here are 12.

 

You

No one wants to hear all about you. See the next subtitle. That's who your audience wants to hear about... themselves. But (and it's a big 'but') they do need to know enough about you to know you are worth paying attention to. So, for a cold proposal, this means using the introduction or cover letter or some other means to establish your credibility - what my dad used to call your bona fides.

Them

This is what they want to know... What's in it for them? Show how you have their best interests in mind with this proposal. You understand their needs and desires and know how to satisfy them better than any alternative solution can.

Focus

Keep your focus on the specific situation. Any sign of standard 'boilerplate' descriptions, arguments, or evidence will make it look less about 'Them' and more about 'anyone'. 

Value

How will your proposal deliver and maximise value to them? The vast majority of business decisions revolve around the capacity to either make money or save money.

Benefits

But there can be other benefits too. Describe the non-financial value your proposal offers - and what this means to them. This, of course, means you need to take time to understand them and their requirements and priorities. 

Emotions

All that hard evidence gives them a reason to make the decision to accept your proposal. But it won't motivate them to do so. For that, you need to tap into their emotions. Find emotional hooks into pride, fear, duty, desire, ambition, loyalty, passion... Emotions drive decisions: reasons justify them.

How

So, you also need to show how your proposal will solve their problem, deliver their joy, or enhance their reputation. Make the link between what they want and what you are proposing as clear, simple, and short as you can. A 15-step sequence from the cause (your proposal) to the effect (their outcome) won't cut it. 

Process

Next they need to know what will happen if (when) they say yes. What will you do, what will they do, and how long would it all take? For confidence that your is the right choice, they need to see a plan that clearly works.

Context

This section lets them understand how your proposal fits into your life and theirs - your business and their own. This shows that you and they are compatible and is the equivalent of the more traditional (cheesy) 'how we are different to the competition'. Of course this differentiates you. It shows how this proposal is right for them and for you.

Business

Don't go all techy on a technical proposal. Remember who you are speaking to. If your audience is a business person or a group of businesspeople, focus on the business. If your audience is software engineers, focus on the business of software engineering: not the hardware. What is their business? That's how to frame your proposal.

Structure

I get it. You have a lot of ideas to get down. But, before you start, develop a structure that makes it compelling for them to follow. If they asked six questions in a sequence, then a great structure is to answer those six questions... in the same sequence. Make it easy for them to say 'yes'.

Quality

Finally remember Mark Anthony's advice: 'The evil that men do lives on. The good is oft' interred with their bones'. People remember your mistakes and easily forget all the good stuff. Make sure you check the quality of your proposal, not once, not twice... Better still, get the pickiest, most pedantic person you know to do it for you. You invested all that time. Now add a little more investment, to avoid throwing it all away!

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What is boldness?

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"About boldness: Some might say “impulsiveness,” yet what is boldness but impulse leavened by calculation?

Daniel Allen Butler

Calculation? Where does that come from?
Experience is where it comes from. 

And what can we say about experience?

Steve Jobs would say it's one of the two coins that we get paid: One is cash, and the other is experience.
Others say it's the accumulated wisdom of all your encounters, good and bad

So, can you be bold without experience to base the calculation?
Yes, but then you are going by the "book" (others experience), or guessing or hoping or, in the worst case: foolish!

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The first rule of data

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You can't have too much data .... correct?

Actually, not correct.

The first rule of data:

• Don't ask for data if you don't know what you are going to do with it

Or, said another way (same rule)

• Don't ask for data which you can not use or act upon

And, your reaction might be: Of course! 

The data plan

You may be shocked to learn that often there is no data plan! 

My experience: In the PMO there are often too many incidents of reports, data accumulation, measurements, inquiries, etc. for which there actually is no plan for what to do with it. 

• Sometimes, it just curiosity; 
• Sometimes you're out of your lane and it's really none of your business to know
• Sometimes it's just blind compliance with a data regulation; 
• Sometimes it's just to have a justification for an analyst job
• Sometimes it's a misguided idea that "there can't be too much data".

The tests:

•  If someone says they need data, the first question is: "How does it add value to what you are doing, and do you have a plan to effectuate that value-add?"
• The second question is: "Do you have a notion of data limits: enough, but not too much to be statistically significant, and control limits for useful -- or not -- metrics."

And information?

Well, the usual definition is that information is data, perhaps multiple data, integrated with context and perhaps interpreted for the current situation.

So, the rule can be extended: if there are not means to process data into information, is the data necessary to be collected?

Bottom line: To state the obvious: always test for value-add before spending resources to collect, process, and disseminate data.

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