Decision Making

Make decisions

Debating the 'best' decision can lead to actually deciding nothing. Good decision making is often a 'teams and timing' thing.

Good decision makers seem to have three key abilities: they gather the appropriate evidence (and ignore irrelevances), weigh it up correctly and make the decision at just the right time.

   Sometimes decision making is a solo activity - say, when you are the only person with all the information necessary to make that decision. On other occasions, we can reach a better quality decision by involving others. In his book The Wisdom of Crowds, columnist James Surowiecki explores how large groups of people can consistently deploy their pooled wisdom to outstrip individuals - no matter how brilliant the individual - in solving problems, fostering innovation and coming to wise decisions.

   When it comes to making the decision at the right time, there is obviously no 'one-size-fits-all' moment. Every decision has to be assessed in its own context. Generally speaking, you'll find it's more important to make the right decision than the 'best' decision. Every decision involves a level of risk, and some decisions are more critical than others to get absolutely right. If there are a number of ways of doing something, and it looks like most of them would work well enough, there's little value to be gained - and much time to be lost - in agonising over finding the best possible solution. On those occasions, just be pragmatic: implement a perfectly satisfactory solution - even if it's not absolutely optimal.

Ken walks past an clothing shop.

Ken : "OMIGOD, THAT COMMEDES GARCONS SUIT IS LOVE!! IT'S ON SALES?! ONLY £450!!!

BUT MY CREDIT CARD IS ALMOST MAXED OUT...ON THE OTHER HAND, THE AGENCY WILL PAY ME THIS FRIDAY..."

Shop Owner : "UM, SIR? WE'RE CLOSING NOW -"

Ken : "NOT UNTIL I BUY THAT SUIT!! HERE TAKE MY MONEY!! TAKE IT!!"

yes, good gentile decision maker, you're in charge! as long as you stay within the rules set for you and you serve the right interests hehehe...

>>2

EW, JEWS!

>>1

Join an movement like Choice Point will be more effective : http://www.choicepointmovement.com/landing

>>3
Dude! Don't steal my game!

I don't understand women. They do and they hate each other. I thought everyone carried O/C spray. Carrying a Trebuchet in the middle of the night and not using it to get home just seems excessive and impossible. Don't get me started on the licensing costs just to legally own it. Pockets are annoying because they stab my sides and I can't even fit a legal sized trebuchet in one. Cargo pants are more comfortable. Saying this out-loud while wearing them has gotten me fired from too many jobs. That's why I carry this t shaped necklace. It lets people know that my imaginary friend can beat yours up.

Conform and rest.

i suggest reading lowenthal, his books are amazing.

you should try to read lowenthal, his books are very good.

you should try to read lowenthal, his books are very good.

you should try to read lowenthal, his books are very good.

Make proactive decisions

Scrutinise customer and business data to come up with the best solutions.

Use this seven-step process to gain a competitive advantage

DO YOU react to situations all the time? With customer and business data at hand, and by turning it into insights, you can now make proactive decisions and switch from reacting to situations to anticipating them.

   The 7-Step Business Analytics Process can help you and your organisation gain a competitive advantage in the marketplace.

   The process can be illustrated through the use of a bank example. Currently, ABC bank feels it is losing too much money to bad six-month personal loans. About 30 per cent of its customers are defaulting on their loan repayments.

   Imagine you are the bank loan manager. You are interested in building a tool that will assist the bank in reducing the amount of money lost due to bad debts. To do this, you use the 7-Step Business Analytics Process:

1. Define the business needs

First, you must understand what business would like to improve on or the problem it wants solved. The goal should be specific and measurable. In the bank's case, it can be: "We want to reduce our rate of bad loans by at least 10 per cent, using a model that predicts which loan applicants are likely to default".

   Once the business goal is set, you can focus on collecting the data that meets this goal. This is usually defined by the business analyst. At this stage, key questions such as, "What data is available?", "How can we use it?" and "Do we have sufficient data?" must be answered.

2. Explore the data

This stage involves conducting data samples and data cleansing, when the analyst is already looking for general patterns and actionable insights that can be derived to achieve the business goal. Before moving to the next stage, you must be confident that the data is of good quality. As the saying goes: Garbage in, garbage out.

   Back to the bank illustration. You (the bank loan manager) and your team collect a sample of representative loans from the past five years, where some of the loans have defaulted (about 30 per cent), most of them not (about 70 per cent).

   You will collect a variety of attributes about each loan application such as credit history, credit amount, saving balance, number of years employed, marital status, gender, age and so on.

3. Analyse the data

At this stage, you will look to see which attributes are related (correlated) to a bad loan by performing correlation analysis. Often, this is when the data is cut, sliced and diced, and different comparisons are made while trying to derive actionable insights from the data.

4. Predict what is likely to happen

To predict which loan applicants are likely to default, you would use a classification model to decide whether the loan applicant is likely to be good or bad. Models such as decision trees and logistic regression are some examples of classification models. Once the model has classified the loan applicants, you need to check whether the rules of the model make sense.

5. Find the best solution

The analyst will run "what-if" scenarios, using the predictive model targets set by managers to determine the best solution, with the given constraints and limitations. The analyst will then select the optimal model solution based on the lower error, management targets and managements intuitive recognition of the model coefficients that are most aligned to the organisation's strategic goal.

6. Make a decision and measure the outcome

The model will then be tested on a sample of new loan applicants and after an appropriate period of time, the analyst will measure whether the business goal was met: Has the bad loan rate been reduced by at least 10 per cent? Is the model accurate enough to deploy on a large scale?

7. Update the system with the results of the decision

In the final stage, the database is updated with the new bad loan rate and the return on investment. Steps 1 to 7 result in an evolving database that is continuously updated as soon as knowledge and new insights are derived. Business Analytics Processes, such as the one illustrated above, enable business users to make proactive data-driven decisions in almost real time, providing a competitive advantage to the organisation.

SHERMAN'S LAGOON   BY JIM TOOMEY

Megan : "FAMILY DECISION TIME. I NEED YOUR HELP."

Sherman : "HUH?

YOU NEVER ASK FOR MY HELP ON ANY FAMILY DECISIONS."

Megan : "AND FOR GOOD REASON. BUT THIS TIME IT'S DIFFERENT.

USUALLY, I CAN MAKE A DECISION WITH 100% CERTAINTY.

BUT IN THOSE RARE INSTANCE WHEN THERE'S A SHADOW OF A DOUBT. YOUR INPUT IS REQUIRED.

THIS IS ONE OF THOSE RARE INSTANCES."

Silence

Sherman : "YOU NEED SOMEBODY TO BLAME IF YOU'RE WRONG."

Megan : "THAT TOO."

www.shermanslagoon.com

2-23 © 2014 Jim Toomey. Dist by King Features Syndicate Inc

even the changelog had kittens in it.