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Fraud Consequences
AZ Fraud Fighter Newsletter 3/14/12


How Safe is Your Business From Fraud? 

Is Fraud Inoculation Possible for a Small Business? 

Part 5 of 10

Working Capital

Inventory replenishment became an intricate chess game as on-the-shelf inventory value in the warehouse quickly dropped from well over $1 million to less than $500,000, causing the purchasing manager major headaches. Many stretched vendors began to do business with this firm on a cash-on-delivery or paid-in-advance basis.


The purchasing manager and the owner made new deals with different publishers to intentionally raise costs by sharing part of the rich margin of regular new publishing with them, entreating them to make units for us in bulk, then holding on to our inventory, doling out product to us as they were paid in cash.


This inventory process is a kind of 'just-in-time' inventory, available whenever cash is fronted, yet we begged and pleaded for these terms instead of dictating them. All the risk for inventory overruns is ours as well, at these new publishing houses. The only real risk faced by these two long-time, friendly suppliers is our bankruptcy, which the regular publishing of new inventory renders increasingly unlikely.


Payroll expenses were trimmed again and again to reduce the bi-weekly consumption of cash in order to maintain sufficient cash for new inventory acquisition. Occupancy expenses followed payroll expenses as the second largest expense line item, so three locations were consolidated into two. Payments to landlords and leaseholders were renegotiated to smaller amounts as the credible threat of filing for bankruptcy (though decreasing over time) became a weapon to extract concessions.


To be continued next newsletter. 


Interesting Fraud Fact -  

The median duration of all frauds studied by the ACFE in their 2010 Report To The Nations is 18 months. But the median duration of financial statement fraud, which are the most costly of occupational frauds, were the longest, lasting a median of 27 months -- from inception to discovery.


Fraud Tip - If your firm distributes payroll checks, make sure the check distributor is not the same person as the one who calculates the periodic amount of each check. Then regularly compare the list of employees paid to the names listed on the payroll check faces. And always count the number of employee checks issued.  


Schedule a Fraud Risk Assessment today. Click here to contact EFM
Caught by the law
Going to jail

Practical Economics:    

Squishy Numbers, Economic Indicators & the Mainstream Media 


Previous Student: 

Actually, I suspect the biggest unknown variable in every model of the dynamic economic forces at work that does not lend itself well to hard data measurement is - Consumer Confidence. We try to put a number on that every month, but is assigning a number truly reflective of reality?


Comments Regarding Soft Data -

I wholeheartedly agree. We try to take all sorts of measurements to predict the economy, but I really think Consumer Confidence might be the most important. If people are confident that they will stay employed, that they will have steady income, then they will be more likely to spend or invest money. Yet measuring this confidence is difficult at best.  


One important piece of the puzzle, as far as making meaningful economic predictions, is knowing something about consumer sentiment or Consumer Confidence. But Consumer Confidence cannot be measured objectively, period.


What we use is something the University of Michigan has developed called the Consumer Confidence Index. Every month, a certain number of consumers are surveyed and asked similar questions. Their answers are tallied and the end result compared to a base of 100 developed in 1982 or thereabouts. However, no matter how much mathematical care we exert, the monthly Consumer Confidence number is still soft data.


Squishy Numbers  

The Consumer Confidence numbers are 'squishy' because they are subjective. But Consumer Confidence numbers are measured every month. That allows for some good comparisons, month to month, which removes some of their squishy nature stiffening up those numbers. However, there are also wide swings (cause unknown) from month to month that are more related to 'mood swings', than anything else. Remember though, one's current mood has much to do with one's current purchases.


The Consumer Confidence number is soft data, while many of the other economic indicators are hard data. The difference is that hard data numbers are counted, like totaling out-of-pocket dollars used or noting the time spent, while soft data numbers are completely subjective, that is, estimated by each person, subjectively, one-by-one.  


For instance, soft data numbers are student survey numbers generated at the end of each university class. If you are asked, "on a scale of 0 to 5, zero being 'never', 5 being 'always', how do you feel about this?", then the response you give is soft dataSoft data is an attempt to measure feelings or happiness or satisfaction or subjective value, etc.


Measuring feelings correctly is hard to do, but not impossible. At least no one in our society thinks such measurement is impossible. However, and this is the critical issue, measuring feelings can be done well or be done poorly. Usually, it is not immediately obvious if the feeling measurement has been done well or not. 


'Hard Data' and 'Soft Data' are NOT similar   

Whereas the number of Americans unemployed at a given time can be counted (then estimated, but we assume the approximation is close and statistics tell us it is) by anyone because hard data is not feeling, but something that is counted, with all the attendant problems of counting. Soft data is never really counted per se as it is non-tangible by definition. Instead, because soft data is an attempt to measure feelings, we first try to identify which feelings we want to measure, then we put a number on those feelings, and then those numbers are tabulated.


There is a huge difference between hard data and soft data. I contend that soft data is almost always more important, but always much more difficult to measure. The reason the University of Michigan survey on Consumer Confidence is important is because the survey is done carefully and the same questions are asked over and over again, every month and every year.  


The rich irony is often soft data is more important to business success than hard data. We recognize that fact when we say a person's gut instinct is great. Or we identify that her intuition is almost always right on. Do employees happily anticipate going to work every day or do they dread it? Do you enjoy talking to your boss or do you try to avoid that person whenever possible? Examples of soft data in the workplace abound. 


Yet actual difference between hard data and soft data illustrates one of my complaints with the academic study of economics. Some economists pretend that since economics can be subject to rigorous mathematical and statistical analysis, therefore, if we always follow the MC = MR rule (or some other economic principle) under every circumstance, then we will never be wrong. If only life were so simple.  


One of the main reasons that economists have many different opinions while using the same information is because many crucial measurements in economics stem from soft data, like Consumer Confidence, which is decidedly NOT hard data.

Mainstream Media Problem 
The worst part of this issue is how the mainstream media treats economic soft data and thus amplifies the reality problem. On a non-stop, 24/7 basis, the economically-challenged mainstream media inundates Americans with soft data masquerading as hard data. In fact, I am sure that most people in the economically-challenged mainstream media have little idea there is a difference. And perhaps those that do know better choose to bask in the power of broadcasting misinformation.     


For instance, on a daily basis, the value of the overall stock market moves up or down based on the new information coming forward that day. Truly the stock market considers  many squishy numbers and issues daily, then the stock market translates both the soft data and the hard data into only hard data -- reflected by a new stock price. But no one besides Warren Buffett seems to have a clue what the exact relationship is. And there are thousands of public companies trading millions of shares every day.  


No one has ever been able to discern exactly why stock values move up and down. Yet often a single slice of the daily news (soft data - e.g. the Greek debt situation worsened) is identified by this or that analyst, then that analyst' opinion is picked up by the economically-challenged mainstream media and confidently deemed the sole culprit causing the up or down movement in the stock price (hard data). This economically unreasonable scenario happens every day.


Likewise, we are constantly bombarded by the economically-challenged mainstream media claiming this soft data poll (usually ignoring relevant statistical issues) to be hard facts or that soft data survey to represent reality, whereas the truth is that what we are being given is tabulated feelings dressed up as hard data. Most people recognize the difference between soft data and hard data, the importance of soft data and the difficulty measuring soft data, but the mainstream media sometimes seems clueless.      



May I conclude with a soft data analysis of my own? "On a scale of 0 to 5, zero being 'not at all', 5 being 'perfectly', how well do you feel the mainstream media is doing at disseminating meaningful information? A generous score from me would be 0.5, or perhaps 10% of the time, a scarcity largely caused by mainstream media confusion between soft data and hard data.   


If you have a lunch group or a breakfast group looking for a dynamic speaker to make a meaningful presentation, then email or call EFM today @ 480-577-6776 to schedule a presentation on Fraud Awareness and Fraud Prevention.
Paul Updike, MBA, CFE, UOP Faculty Practitioner
Executive Financial Management
(480) 577-6776
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