Access Company Credit Risk Using Internet Resources

Granting a company the right to pay for a service or product at some time after you have delivered the service or product involves a risk that the company will not pay what is due.  Resources on the Internet might help you in assessing the credit worthiness of that company and help you decide on whether selling to that company is a good idea. 

This blog identifies some of these resources.  Some of the resources do not require a fee but others do.  All involve in some way a database with historic information related to the company.  Such historic information is useful for assessing the credit worthiness of the potential customer.  

The expense of using these resources, in terms of your time plus any fees, probably can be kept to less than two to three hundred dollars per customer, perhaps much less. This seems like a small price to pay to weed out potential non-paying companies when the cost of the service or product to you is high enough.

What follows is a suggested sequence of using the Internet to obtain information on a company and its credit worthiness.

Maryland, and probably most other states, offers access to Maryland-registered company information from its websites.   At this Maryland site (click here), information can easily be found on such things as when the company was formed, the value of personal property (based on personal property tax returns), and whether the company is in good standing for paying it personal property tax.  Also from this site, a search of UCC filings will show those filed against assets owned by the company.  These filings might be useful in evaluating the debt status of a company and perhaps how others view the credit risk of the company.

Also in Maryland, and probably other states, you can search  for the real (land and structures) property a company owns and the value of that property as assessed for real property tax purposes (click here to go to the site where a search can be made).

The American Bankruptcy Institute has a site (click here) apparently still being developed (i.e., in beta status) that will search several databases simultaneously for bankruptcy and other legal news related to the company of interest.  Knowing that a company has gone through bankruptcy, and/or other legal proceedings, can be useful in evaluating the credit worthiness of the company.

The United States Government maintains the PACER (Public Access to Court Electronic Records) system (click here to go to this system’s website).  At the site, you can search US court cases that a company has been involved in.  Fees do apply.  Court cases can provide insights into a company’s financial and other transactions.

Experian (click here), Equifax (click here), and TransUnion (click here) offer reports on small businesses that assess the credit worthiness of the businesses.  Fees for basic reports range from $35 to $100, and more.

D&B (Dun & Bradstreet) offers reports starting at $62  that provide information on a company’s payment history.  Click here for details.

LexisNexis, which maintains or has access to large numbers of databases, offers a small business credit risk service based on LexisNexis use of those data bases (click here to go to the service).  LexisNexis also offers a service that will search not only state records of UCC filings but also state records showing state tax liens against companies, another indicator of a company’s ability or willingness to pay on time (click here to go to the service) .

Spending some time, and in some cases fees, using such Internet resources as identified above could fine risks associated with the credit worthiness of a company, and help you decide on whether you want the company to be a customer.

Using Force Field Analysis for Change

Recently I was in Mali working with a women’s rice growing cooperative to help them improve their accounting.  During this period, I had a chance to assess and become familiar with their situation and their desire to be more profitable.  Their lack of profitability is a concern for them.  They want more profits, more wealth generation.

A conclusion that I came to is that the cooperative needs to be run more like a business, needs to incorporate sound business management practices, in order to become profitable.  Because it seems to me a change is needed, I decided to learn more about force field analysis by writing this blog and apply the concept of force filed analysis to the suggested change for the cooperative.

At the risk of over-simplifying, force field analysis evaluates the forces that promote a change and the forces that oppose the change.  The analysis tries to identify all those relevant forces that promote and those that oppose the change

Here is a list of factors that I came up with that promote the cooperative in Mali to being more like a business:

1.  Lack of profit as a cooperative – 3;

2.  Recognition that as a business, profits are more likely – 4;

3.  A better work environment, and other benefits, for cooperative members when the cooperative is run more like a business. – 3.

For these three factors that promote the change, I have assigned a weight to the importance of the factor in promoting (leading to) a change.   The weight is on a 1 to 5 scale, with 5 being of the highest importance.   The total weight of factors supporting a change is 10 (3 + 4 + 3).

Here is a list of factors that oppose the cooperative being more like a business:

1.  Lack of business skills and practice know-how – 4;

2.  Traditional practices and habits of behaving as individuals in decision making and action in rice growing versus company decision making and behavior – 5;

3.  Lack of concepts on assigned roles and company organizational structure – 3.

The total weight of factors opposing a change is 12 (4 + 5 + 3).

Now for some analysis on the above lists and what they might mean and what they suggest.

First, the above lists are based strictly on my experiences while in Mali teaching the cooperative accounting and evaluating their situation.  The correctness of the above lists is therefore constrained by whatever skills and experiences I have in the evaluation.

I believe the first obvious conclusion to reach from the above lists is the cooperative is not going to change to being more business-like on the basis of the current forces for and against that are in place.  The against forces are stronger then the for forces.  So, actions and interventions need to occur if a change is to take place.  The above lists can help guide on what these actions and interventions might be.   An approach is to create a greater weight for each of the for factors and a lesser weight for each of the against factors.

The factor with the greatest weight (5) and therefore draws the most attention is the against factor - traditional practices and habits of behaving as individuals in decision-making and action in rice growing versus company decision making and behavior.   How do we reduce this weight?  Like many of the other factors, both for and against, training is an important action to take.  But, now we recognize one type of training should relate to the advantages of group decision-making; collaboration; team building; advantages of group versus individual performance, and similar concepts.  Such concepts relate to changing traditional practices and habits of behaving as individuals.

Training is also important to reduce the other against forces.  Through creating the lists, we now know better what the training should focus on.  

For the factors that promote change to being more like a business, training on what profits are, how to measure them, for example, by using correct accounting and creating income statements, should be emphasized.  An accounting system should be implemented with the goal of showing annual profits.  Using an accounting system should help the cooperative to be more business-like.

Company organizational structure can bring benefit to the participants in a company versus when the members go alone, which a problem with the current cooperative situation.   Such benefits include: specialization of duties, which promote greater success for the organization versus when individuals act alone and better collaboration and coordination on the use of the available resources, easing the burden that can exist when individuals go alone.    Specialized training should be planned and presented demonstrating these concepts and the results of these benefits to members.

Force field analysis strikes me as a relatively simple but powerful tool to help in implementing a needed change.  Hopefully, the above has demonstrated this. 

More can be found about the concept and use of force field analysis at the MindTools website. Click here to go to this website.

Use a Twitter Tweet Dashboard to Help Manage Your Business

An enormous amount of information flows down the Twitter electronic pike as tweets.   This continuous flow from thousands of tweeters – individual, company, and other organizational types – represents a unique source of information.  It seems to me that there has never been anything like what this flow of tweets represents with respect to information availability.

It is technically relatively easy to select a specific topic, for example, employee performance, and then to pull (filter) from the Twitter flow many tweets with relevant information on the topic “employee performance”.   If one is seeking what others know about employee performance, using Twitter as one source of information would be easy and likely productive.

Although, as stated above, gaining access to tweets on specific topics is relatively easy, what should one do who is interested in a broader subject, such as human resource management, under which employee performance is but one subtopic?  In other words, how does one filter Twitter for all tweets with information on the various subtopics that make up a broad subject area such as human resource management? 

An answer that I have come up with uses the idea of a dashboard consisting of several filters, each filter on a specific subtopic within the broad subject area.  Once set up, the dashboard can easily be brought up as a webpage and then each filter on a specific subtopic will be available to drill down for details in the tweets on that subtopic.  The collective tweet fitters will cover many, if not most, of the subtopics that make up the broad subject area of interest.

This idea of a dashboard of Twitter tweets seems to me to offer the possibility of being a good tool in managing various broad subject areas in a company.   Besides human resource management, other areas might include: financial management; benchmarking; sector analysis; environmental issues; governmental issues; and country and regional informational needs.

A dash board concept is used extensively in financial management of a company where the various components of a financial dashboard represent various financial and accounting data relevant to the company.  Collectively, the various filtered data (on the dash board) gives an overview of the financial condition of the company. 

Hopefully, the collective filters of tweets on subtopics of a broad area, such as human resource management, will also give useful information in managing the general area in a way not possible otherwise. 

Click here to go a version of this blog which shows the “Human Resource Management Twitter Tweet Dashboard”.  Shown at the bottom of the page are 7 subtopic Twitter filters making up the dashboard.  These filters were set up using Twitter creation tools on one of their web pages.   The subtopic filtered is shown at the top in the presentation box.   The presentation box presents tweets in real time as they are submitted in Twitter, and will cover tweets in the recent past (e.g. several days).   Clicking the link “Join the discussion” in the presentation box will bring up a complete list of the tweets related to the subtopic that have appeared in the recent past.

Twilert, a Twitter App, Should be Useful to Support Decision Making

Twilert is a free web app that enables you to receive selected Twitter tweets by email.  The tweets sent to you will have the keywords in them that you select. Twilert, which is easy to set up and to use, can provide you selected information that flows through the Twitter system.  This information could be useful to you in decision-making.

For example, many federal, state, and local government agencies now “tweet” (send out electronic messages) using Twitter.  These tweets contain information about the agencies’ services and actions that the agencies feel may be of value to the public, the users of its services and recipients of its actions.    These tweets can contain such information as pending regulatory and compliance requirements, information that is valuable for businesses to know about as soon as possible.  Twitter is a very efficient and effective method for agencies to electronically distribute important information.  And, for companies, who can benefit from knowing this information as soon as possible, using a service like Twilert could be very useful in being alerted to these tweets.

Monitoring Twitter for government regulations is just one example of what information, which flows down the Twitter electronic pipe, can be monitored by a company.   Other examples include:  software used by the company; products produced; services offered; markets targeted; retail products being considered for sale; and likely many others.

Perfecting and using skills to extract useful information from million of tweets that flow down the Twitter message pike will likely prove to provide many advantages to a company.  One easy to set up and use tool to begin monitoring Twitter tweets is Twilert.  Click here to go to the Twilert website.  Check it out.

Using a Decision Tree Analysis for Insights on Marketing Expenditures

In my last blog below, I wrote on the use of What-If Analysis to reach conclusions about pricing by a small professional services company.

Data generated by the Excel What-If Analysis Tool for the below article can be nicely used to gain insights on marketing expenditures, when used with decision tree analysis. 

For example, assume that the company in year 1 has a $90 per hour fee it charges, a demand of 800 hours, a fixed cost of $10,000 (rent, utilities, office expenses, etc, but not including the salary), a variable cost equal to 30% of revenues (which corresponds to US Census survey data that shows that professional service companies have an average 70% gross profit margin percentage), and breakeven profit (profit = $0).   At these amounts, the company is able to pay a $40,000 salary (as shown by What-If Analysis).

Now, the company wants to increase the $40,000 salary that it can pay in year 2 by increasing the demand above 800 hours, while keeping the $90 per hour fee the same.  So the company decides to increase marketing expenditures to try to increase demand.  How much should the company increase the marketing expenditures?

The use of the  analytical tool, decision tree analysis, can help answer this question.  A major difficulty in answering the question is predicting the increased demand with certainty.  To counter this uncertainty, the decision tree analysis approach is to assign probabilities to possible demand increases resulting from marketing.  

Here is an explanation.  Assume that one outcome of the marketing program is that it is not very successful.  In using decision tree analysis for this outcome, I have defined the outcome - not very successful - as: 80% probability that there is no demand increase; 20% probability that there is sufficient demand increase to increase the revenue (and therefore salary) from $40,000 to $50,000, and there is no probability to increase the revenue (salary) by $60,000 or $70,000.  With these probabilities, the expected revenue increase in year 2 can be computed to be $2,000 [from $40,000 (year 1) to $42,000 in year 2].    This is computed by using this formula: 0.8 x $40,000 + 0.2 x $50,000.   In other words, there is an 80% probability that the revenue (salary) will remain at $40,000 and a 20% probability that the revenue (salary) will go to $50,000, so that the most likely result is $42,000 (assuming 80% and 20% are correct). 

Now we can compute the likely revenue increases in three other possible demand increase outcomes: moderate success in more demand; good success in more demand; and very successful increase in more demand.   The computations for each of these three possible outcomes, done as above for the not very successful outcome, give these increases from $40,000 in year 1 to: $46,250 (moderate success); $48,250 (good success), and $55,000 (very successful), in year 2.   These increase values depend on the probabilities that I have assigned to the possible outcomes. 

These three possible demand outcomes are given percentage probabilities for each of the four revenue (salary) outcomes: $40,000; 50,000; $60,000; and $70,000.  These percentages are:

1. Moderate success:  $40,000 – 50%; $50,000 – 40%; $60,000 – 7.5%; $70,000 – 2.5%.

2. Good success:   $40,000 – 30%; $50,000 – 60%; $60,000 – 7.5%; $70,000 – 2.5%.

3. Very successful:  $40,000 – 10%; $50,000 – 40%; $60,000 – 40%; $70,000 – 10%.  These percentages need to be selected by the company.

The decision tree analysis is greatly assisted by first doing the What-If Analysis, which will give the demand hours needed for various increases in revenues (salaries).  Knowing these hours help in deciding on the probability that marketing expenditures can reach these number of hours.   The demand levels for these revenues (salaries) are:  $40,000 – 800 hours; $50,000 – 952 hours; $60,000 – 1,111 hours; and $70,000 – 1,270 hours.

The results now give us some insight into how much the company should increase the marketing expenditure.  Probably less than $15,000 should be spent, since it is unlikely that a revenue increase will be greater than $15,000 (that is the amount of revenue increase predicted in a very successful marketing campaign).   A conservative decision for marketing expenditures would be less than $2,000, since this is the amount of revenue increase predicted for a not very successful marketing campaign.  For year 2, the best expenditure is probably between these two amounts.  Year 2’s results should help in better selecting the outcome probabilities in subsequent years, if the marketing campaign continues.

The Mind Tools website (click here) provides an explanation, with an example, of decision tree analysis.

Pricing Decisions for Professional Service Providers Using Excel’s What-If Analysis Tool

(Salary amounts modified on August 1, 2012 due to error discovered in initial computations.)

A problem for small professional services companies in starting up their businesses can be what price (fee) to charge for the services provided.   The demand for the services and what other similar (same experienced, skills, etc) providers charge are often uncertain.  Using Excel’s What-If Analysis Tool can provide a baseline fee level for various demand hours (total billable hours) at an assumed variable cost and fixed cost (including an expected salary) and at a breakeven point ($0 profit).

A lowest baseline fee level needed to reach a certain salary at an assumed demand, variable and fixed costs, and profit = $0 (breakeven point) should be useful for professional service providers to know.  Knowing a lowest baseline fee level removes some uncertainty about the lower limit of a fee to charge.  With this knowledge, the service provider should be more confident that any fee below a fee determined by using the What-If Analysis Tool will not provide an expected (needed) salary.  This does not mean that this lowest baseline fee is the fee that should be used.  What is met is that the fee is the lowest fee that should be considered.  Considering higher fees depends on many uncertain factors, not the least of which is demand at various fee levels, which a tool like What-If Analysis will not be able to provide much help with.

Using Excel’s What-If Analysis, I was able to show, at 1,200 hours of demand (total billable hours), a fixed cost of $10,000 (rent, utilities, office expenses, etc.), a variable cost equal to 30% of revenues (which corresponds to US Census survey data that shows that professional service companies have an average 70% gross profit margin percentage), and at a breakeven point (profit = $0), the following:

1.  With an additional fixed cost of $30,000 (salary), the fee needs to be from $45 to $50 per hour; at an additional fixed cost of $40,000 (salary), the fee needs to be from $55 to $60 per hour; at a additional fixed cost of $50,000 (salary), the fee needs to be $70 to $75; and at an additional fixed cost of $60,000 (salary), the fee needs to be from $80 to $85 per hour, in order to reach the stated salary. 

2.  But, decreasing the demand to 800 hours, the corresponding required fees for the above stated additional fixed costs (salaries) need to be:  $70 to $75; $85 to $90; $105 to $110: and $125.

So, if a professional service provider expects a $50,000 salary and will have a demand equal to 1,200 hours, and has $10,000 of other fixed costs (in addition to the salary expectation), and assumes a 70% gross profit margin percentage, a fee of $70 to $75 per hour will obtain the expected $50,000 salary.  Also, it is possible that a professional service provider will be very intolerant of continuing in business at a salary level lower than $30,000 to $40,000.  If yes, a minimum fee for such a service provider would be $45 to $60 per hour, given the above stated conditions.  (In other words, a $45 to $50 per hour fee provides a $30,000 salary, at the conditions stated.)  This fee range would go down at higher demand levels, and up at lower demand levels, again, given the conditions stated above. 

In addition to suggesting a lowest baseline fee to use, the What-If Analysis Tool can generate demand (number of total billable hours) levels that will provide a certain salary, at a fee amount.  One possible use of such data might be adjusting a fee on a year to year basis.  For example, if after year 1, a certain salary is achieved at one fee and demand, What-If Analysis results will show how much a drop-off in demand can be tolerated in the next year when the fee is raised (assuming a raise will lead to a lower demand) yet obtain the same salary as  in the previous year.  

For those interested in using Excel’s What-If Analysis Tool (available within standard versions of Excel), many websites can be found that provide information on using the tool.  One such website (click here) provides instruction, by Wayne Winston, on setting up and using What-If Analysis, with an application description similar to the application discussed above.

The analysis that I did with Excel’s What-If Analysis Tool, a summary of which is provided above, I believe shows that the tool can be very useful in decision making.   Some thought has to go into the details of what is desired.  Then the tool needs to be tested based on the analysis of these details to determine if useful data is generated that helps in decisions that needs to be made.

Concentrate on Coaching and Organizational Goals in Employee Feedback

What companies should communicate to employees about employee performance is a major area of management research and analysis.  Searching the Internet and academic article databases on such terms as employee, performance, evaluation, strategy, and alignment will find hundreds of examples of this research, analysis, and discussions about employee performance feedback.  Much of what is found in recent information recommends changes in the traditional supervisor to employee evaluation, assessment, and rating schemes in practice for dozens of years.

One article found at the Bersin & Associates website provides what seems to me as an excellent overview of the changes being recommended in employee performance feedback.  Click here to read this article.  This article does not eliminate the traditional supervisor to employee performance assessments, but indicates that this traditional practice is only one of the goals of employee feedback, and is a less important contributor to the company’s success than other goals for employee feedback.  These other goals deal not with past performance of the employee, as traditional assessments do, but with aligning the employee’s future performance in ways that support company strategic goals.

Therefore, the major objective of supervisor to employee feedback and supervisor and employee goals for this feedback is not past performance but future directions.  The supervisor now has the role of serving as a coach moving the employee in the direction of acquiring the skills, understanding, motivation, and activities aligned with the company’s strategic goals.

Consider as an example to demonstrate this forward-looking, coaching-management perspective of supervisor-employee feedback, a small company and its accounting function.  Assume the company has three strategic goals:  increased revenues; increased profits; and better customer and vendor relations.  The accounting department would then develop a set of goals for its function that support the company’s strategic goals.  These accounting goals might be: customer and vendor evaluations and analysis; cost analysis; and sales analysis.  Now supervisor to accounting personnel feedback sessions will have a new objective – the needed individual actions, competencies, and analysis to meet the three accounting department goals (which are tied to the company’s goals).

The traditional supervisor-employee work assessments still are needed, but with a lot less importance.  Its importance is now primarily only to screen out those employees who need to be terminated.  All other employees are accepted as worthy in the ways that they are worthy.  These employees are given encouragement and coaching to increase their worthiness, and are asked to set personal goals related to the accounting department’s goals.