Averages And How Deceptive a Word That Is!

Recently I attended our local Mayor’s Breakfast where the Mayor gave an update on the Town Council’s plan for the upcoming years.  During that discussion, the Mayor brought up some statistics about the area.  Namely, she brought up the average household income.

Now, the area where I live is quite diverse in households.  We are located just north of a very large metropolitan area and thus many of the communities in our town are bedroom communities.  We also have a very large rural aspect, with farms of varying livestock and crops.  Lastly, we also have many homes that belong to the rich and wealthy.  In fact, I have been told our town is the location of one of the most expensive houses in Canada.

To get back to the average household income:  according to our Mayor, this is about $113 000.  That sounds pretty good and she used that number to discuss the type of industry, education and retail requirements of the town.  Now, from a stats perspective, I’d like to show you four different charts.  Each chart represents 100 data points, with an average of approximately $100 000.

Chart 1: Average is $100K and the distribution in tight – everyone is very close to $100K.

Chart 2: Average is $100K and the distribution is looser - have some people with no income and some with a household income closer to $300K

 Chart 3: Average is again approximately $100K but we have more people with an income of less than $100K but they are being offset by those with incomes greater than $300K

 

Chart 4: Okay, average is closer to $125K but here you can see that over 75 of the 100 data points have an income less than $100K and nobody has an income between $100K and $350K.  Yet those who have an income greater than $350K offset those lower incomes dramatically.

Now which one of these scenarios more accurately represent my local area?  I would imagine somewhat of a blend between Chart 2 and Chart 3.

Populations statistics is not the only place this kind of variation in data all with the same average can occur.  This also occurs with machine performance – you may on average be able to fill 250ml in your carton but how many are underweights and how many are overweights?  Are you filling well above the 250ml to make sure your underweights fit within government regulations?  How much profit are you losing to make sure you range of weights doesn’t go below T1 or T2?

Stop the Creep – or at least contain it!

All projects change – may be not quite a truism but close enough!  Life happens and it WILL have an effect on your project.

Upfront planning can help develop contingency planning and well as conducting an FMEA (Failure Modes Effects Analysis) to anticipate some events (i.e. Customs officers holding up equipment at the border).  Mother Nature though has been known to be unpredictable, delaying shipments, changing costs and even damaging equipment.  Imagine those companies in flooded Queensland, Australia who have literally seen their plants go down the river!

Once a project has been initiated, a huge challenge for any project team is sticking to the original scope.  While the previous examples have been more of an emergency, once the projects begins, many more people become involved and start wanting things added or changed.  These changes to the project are termed “scope creep”.

During the planning phase, a stakeholder analysis can help identify those people who may want to see a slightly different outcome or who will place a higher priority on different aspects of the project.  This again allows the team to develop a contingency strategy.  Even more important at this time is to develop a scope change strategy.

A scope change strategy can be broken into 3 parts:

1. Approvals – who needs to agree to the change in order for it to go ahead
2. Criteria – what conditions have to be met to accept the change (ie safety, cost, quality)
3. Impact – analysis of the impact it will have on the 3 success criteria; cost, performance and timeline

Communicating the strategy to team members and stakeholders will help reduce tension and ensure a fair process is being used, making things overall go smoothly.

No One Wants a Lemon

Running a capital project without spending the time to do upfront planning is like going to a random car lot and choosing the first red car you see – chances are you may end up with a lemon on your hands!

It is generally accepted that success of a capital project is defined as:

1. Project stays within budget
2. Projects finishes within schedule
3. Final, installed, commissioned project meets performance objectives

These criteria have a tight interrelationship and when one goes out of balance, the others generally follow.  For example, the timeline is shortened, so costs likely will go up due to overtime and expediting costs, shortcuts may have to be made and inferior equipment chosen.

Upfront planning is one of the most critical pieces to improving the capital process and increasing the number of successful projects; more projects that come in on time, on budget and do what they are supposed to do.  If you look at your company’s capital project performance, how long was spent in the planning phase?  Can you relate this to the number of successful projects, how many actually closed versus the ones that were cancelled?  

Each project is different with a different level of complexity so measuring time may not necessarily be the best measure of upfront planning.  The better measure is evaluating the outputs of the planning stage.  Where project expectations and goals clear, understood, agreed upon by all and achievable?  In other words, were they SMART (Specific, Measureable, Achievable, Realistic, Timebound)?

Just like buying a car, if you don’t know what you want when you start shopping, you may just end up with a lemon and no one wants a lemon car!