Why Use Comps when We Live in an Age of Data Driven LSTMS and Analytics?

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Retail is an odd topic for this blog but I have a part time job. Interestingly, besides the fact you can make $20 – 25 per hour in ways I will not reveal, stores are stuck using comps and outdated mechanisms to determine success. In other words, mid-level managers are stuck in the dark ages.

Comps are horrible in multiple ways:

  • they fail to take into account the current corporate climate
  • they refuse to take into account sales from a previous year
  • they fail to take into account shortages in supply, price increases, and other factors
  • they are generally inaccurate and about as useful as the customer rating scale recently proven ineffective
  • an entire book worth of problems

Take into account a store in a chain where business is down 10.5 percent, that just lost a major sponsor, and recently saw a relatively poor general manager create staffing and customer service issues. Comps do not take into consideration any of these factors.

There are much better ways to examine whether specific practices are providing useful results and whether a store is gaining ground, remaining the same, or giving up.

Time Series Analysis

Time series analysis is a much more capable tool in retail. Stock investors already perform this type of analysis to predict when a chain will succeed. Why can’t the mid-level management receive the same information?

A time series analysis is climate driven. It allows managers to predict what sales should be for a given day and time frame and then examine whether that day was an anomaly.

Variable Selection

One area where retail fails is in variable selection. Just accounting for sales is really not enough to make a good prediction.

Stores should consider:

  • the day of the week
  • the month
  • whether the day was special (e.g. sponsored football game, holiday)
  • price of goods and deltas for the price of goods
  • price of raw materials and the price of raw materials
  • general demand
  • types of products being offered
  • any shortage of raw material
  • any shortage of staff

Better Linear Regression Based Decision Making

Unfortunately, data collection is often poor in the retail space. A company may keep track of comps and sales without using any other relevant variables or information. The company may not even store information beyond a certain time frame.

In this instance, powerful tools such as the venerable LSTM based neural network may not be feasible. However, it may be possible to use a linear regression model to predict sales.

Linear regression models are useful in both predicting sales and determining the number of standard deviations the actual result was from the reported result. Anyone with a passing grade and an undergraduate level of mathematics learned to create a solid model and trim variables for the most accurate results using more than intuition.

Still, such models do not change based on prior performance. They also require keep track of more variables than just sales data to be most accurate.

Even more problematic is the use of multiple factorizable variables. Using too many factorized variables will lead to poorly performing models. Poorly performing models lead to inappropriate decisions. Inappropriate decisions will destroy your company.

Power Up Through LSTMS

LSTMS are powerful devices capable of tracking variables over time while avoiding much of the factorization problem. Through a Bayesian approach, they predict information based on events from the past.

These models take into account patterns over time and are influenced by events from a previous day. They are useful in the same way as regression analysis but are impacted by current results.

Being Bayesian, an LSTM can be built in chunks and updated in real time, providing less need for maintenance and increasingly better performance.

Marketing Use Case as an Example

Predictive analytics and reporting are extremely useful in developing a marketing strategy, something often overlooked today.

By combining predictive algorithms with sales, promotions, and strategies, it is possible to ascertain whether there was an actual impact from using an algorithm. For instance, did a certain promotion generate more revenue or sales?

These questions posed over time (more than 32 days would be best), can prove the effectiveness of a program. They can reveal where to advertise to, how to advertise, and where to place the creative efforts of marketing and sales to best generate revenue.

When managers are given effective graphics and explanations for numbers based on these algorithms, they gain the power to determine optimal marketing plans. Remember, there is a reason business and marketing are considered a little scientific.

Conclusion

Comps suck. Stop using them to gauge success. They are illogical oddities from an era where money was easy and simple changes brought in revenue (pre 2008).

Companies should look to analytics and data science to drive sales and prove their results.

 

Worst Personality Types for Any Workplace

Creating a company with a passable office culture is difficult at best. The last thing anyone needs are toxic personalities. There are two such personalities that stand out for their ability to ruin corporate cultures. This article offers two examples of these personalities and proffers a way to resolve them.

Sadly, I have personally dealt with these toxic types in 66 percent of the positions I have held. Interestingly, not only have I landed well paid jobs at the other 33 percent but they are also industry leaders simply for not putting up with these types or any other form of  lackadaisical behavior.

Passive Aggressive

The passive aggressive may actually be the most difficult problem to spot in the office. These people tend to bottle up emotions, releasing them in small often manipulable spurts. Often, the passive aggressive exhibits signs of social inhibition, failure to perform basic tasks albeit this could also be related to a pure lack of knowledge, care, and skill as well.

Rather than helping improve office culture and addressing problems to bring up productivity, passive aggressive people will smile and lie until a problem becomes insurmountable.  They also display difficult working with other personality types.

Consider the following actual example:

A 15 year passive aggressive veteran with very little actual skill has found her way into various positions by being able to avoid conflict. She would never pass a phone screening and works at companies earning one seventh of their competitors revenue.

The passive aggressive decides she does not like working with a hard working, creative type and dislikes the massive amount of actual data coming her way. Despite the fact that this data is clean and dealt with quickly as well as being a major part of company plans, she lets the information sit until it has been archived and then asks why it does not appear to exist despite the notification she received three months prior. She ‘wonders’ why there is new data in place of the old data. In reality, the old data was replaced 12 times.

Another actual example would be an employee who dislikes someone who solves multiple issues in a single blow and will simply act like everything is fine while continuously complaining behind that employees back, hardly working, smoking pot in the parking lot, and drinking on the job to accommodate many other issues. Meanwhile, the number of tickets in the system goes into free-fall as the despised employee completes 50 percent of the tickets every week. Instead of gaining 8 tickets per week, the company is suddenly tackling their backlog.

Selfish

The selfish employee is equally horrible, driving down productivity and needing to be dealt with immediately. They are not team players, lie to get their way, and often perform poorly. They can cause sales to drop by as much as 50 percent depending on the power they obtain.

For example:

A sociopath and manager is in power simply out of sheer force of personality. Within months of ignoring client requests, being consistently rude, and throwing others under the bus, this individual has caused the majority of customers to flee. The company is now 50 percent below the previous year’s revenue.

Listen and Purge

The best way to deal with a passive aggressive and possibly the most overlooked aspect of management is actually listening to all of your  employees and making an actual effort to understand what is going on at your office. This holds whether or not you are in IT. These personality types must be purged for an office to operate at optimal efficiency.

It is important not to confuse the two personalities as seeing many employees as passive aggressive may actually be a sign of pure selfishness by someone in power. Get out there and kick some ass!!!