Five People One Hat

I recently visited with a Director of Marketing at a charitable startup, and he shared that his title sounds impressive, but his roles can vary from web developer, customer service representative, contract manager, warehouse fulfillment person, to janitor, depending on the day and need.  Essentially, one person is fulfilling many different roles, and any issues across multiple functions are most likely going to be handled by the exact same person.  In this scenario there is no cross-talk, no second-guessing, no conflicting information.

By contrast, in larger organizations, one hat can be worn by many people.  Five different data-entry associates will tell you five different ways to process paperwork.  When someone downstream needs to act on the information that was entered and has a question, who does she turn to for help?  The person who produced the discrepancy may not necessarily be the person doing the troubleshooting.  Time is wasted in tracking down the person who made the error, understanding what went wrong, fixing the error, notifying the person downstream that the issue has been rectified, so work can resume.

In both scenarios – effort and work is suboptimal from an efficiency perspective:

  1. One person doing multiple things cannot be the expert at everything.  There are “switching costs” when a person has to put down one thing in order to work on something entirely different.
  2. Multiple people doing the same thing, but with slight variations, can lead to confusion when someone downstream receives something unexpected.

Resolving situation 1 may be a matter of time management and prioritization.  Resolving situation 2 can be much more involved because more people are involved.  Consider the following questions when when evaluating a process:

  • How did the error get introduced in the first place?  Systemic error or human error.
  • How does the output from this function impact downstream functions?
  • What are best practices to completing the task so everyone can benefit from a common approach?

Standardizing a process so it can be repeated and measured is one way to reduce the variance that occurs naturally when more than one person is tasked to perform the same function.  The benefits of standardization are a reduced variety of errors, which speeds up resolution and less confusion downstream.  Being able to measure a process also brings more visibility in managing a process – which leads to greater efficiencies and reduced costs.

To tie everything back to the Director of Marketing – variation in completing tasks is not as much of an issue since one person is generally doing everything from beginning to end.  The practice of one person doing everything may be a necessity, however, it is not sustainable, and when new people come on board they will sure ask: “What is the best way to complete this task?”



Big Data and what it means for your business

“Big Data” has become a significant force in the business community, but what does Big Data actually mean for your business?  According to a contributor at Forbes, the definition has morphed over time – so there is not a consensus on one definition of Big Data.  In our observations, Big Data has can have a positive impact on business performance for those who know how to harness the information.

As a consumer, Big Data means the companies you do business with (grocery stores, retailers, online shopping) collect information to gain insights on your behavior.  With your permission (through loyalty programs, etc), companies will tag transactions to your account in order to find patterns in the things that you buy or do, and in aggregate across all customers.  A classic example is that diapers and beer purchases are closely correlated.  Some experts believe this is because when Daddy is sent to the store to buy diapers, he also picks up something for himself.  Another, more modern, example is that search engines collect information about your search history in order to provide targeted advertising.

As a business, Big Data means it’s possible to gain insights into behaviors of your market, vendors, customers, and internal operations.  If you have strategic questions such as:

  • Where are your customers concentrated geographically?
  • What are the buying cycles in your market?
  • What is the reason for the spike in customer returns this period?

Data can put you on a path to finding a solution, as long as you’re measuring the right things.  It’s important to realize that Data by itself is meaningless.  It requires skill, domain expertise, and curiosity to understand patterns in data, which is why titles such as “Chief Data Scientist” or “Director of Analytics” exist.  If these titles seem superfluous, try the following exercise on your own; it may give you a better appreciation for the importance of skill and domain experience.

Exercise: Consolidating Purchases

Many companies would love to save on costs, and one approach is to negotiate better pricing for critical purchases. To better understand if it’s even worth pursuing such an effort, you will want to first answer these questions, probably by going through your own purchasing history data:

  • Who are your largest vendors by volume? By dollars spent?
  • Do you have secondary or tertiary suppliers?  How reliable are they?
  • What is the shape of your purchasing cycle?  Is it cyclical, constant, seasonal?
  • Are you anticipating an increase, decrease, or constant rate of purchases for the next year?

Understanding how and when you make purchases can equip you with more information to be in a better position when it’s time to decide on renewing or selecting a new vendor.  It will also help you to understand if the purchasing function is in alignment with other downstream functions.

There is value in your data; the trick is asking the right questions and having the skill and domain expertise to make sense of it all.