Guest post from Kurt Peckman, Program Director, IBM Predictive Analytics
Last Friday I took a different train into my office here in Chicago.
This particular station has a diner located right next door and within steps of where I would be catching my train. They only serve breakfast and lunch and it immediately hits me that I’ve stumbled upon a diner with an optimized location and manufacturing schedule.
Speaking of which, I had optimized my wait time for my train. No gross surplus of minutes to waste on the platform; no deficit of time causing a heart attack-inducing sprint from my car to the train. I immediately headed to the diner.
The waitress, who I’ve never met before today, immediately greeted me with, “Hi, honey… $1 egg sandwich today?”
I didn’t fall for the “honey” play. I’m old enough to know that any good waitress worth her salt will refer to me as: honey, sugar, handsome, and the like in an attempt to up-sell me from coffee to coffee plus. And given my experience in up-selling myself (discussed in my last blog) I was naturally on guard.
However, I was very, very intrigued by the price of the $1 dollar egg sandwich.
I said, “No, thanks,” which was tough to do. I love egg sandwiches and one dollar is a heck of a deal for a diner-based product. (Notice the use of the word “deal” and not “price,” which implies “value” to me.) I am trying really hard not to eat so many egg sandwiches so I declined. But, the critical fact in this story is that I paid $1.75 for a cup of coffee.
Secretly, what I really wanted to do was take the entire day off of work to interview “Flo” the waitress (my customer service rep), the chef, and other patrons about the implications of the $1 egg sandwich. I especially wanted to interview the owner (who I think was sitting in the corner reading a paper) as to how the execution of the egg sandwich is tied to his overall business strategy.
How was that price determined? Is it an optimized price? Can a diner really make a profit on a $1 egg sandwich? If so, does it include the cost of all goods: materials, labor, overhead (e.g., utilities, wear and tear on the grill, depreciation on the spatula, etc.)?
Or was the pricing objective pull marketing for the diner? The deal didn’t prompt me to go into the diner, and I’m not even sure there was a sign out front stating the terms of the deal. But, there was signage inside that I realized only after she pitched the deal. Now my mind was spinning.
Is Friday the best day for the egg sandwich promotion? Is this an optimized campaign – right offer, price, channel, day and time? I didn’t even get a chance to ask if every Friday is a $1 egg sandwich day. If so, I might be inclined to invite my colleague Bob (who regularly commutes to/from this station) about the end-of-week-deal at this diner.
Given my love of egg sandwiches, I might even be tempted to take to social media to sing the praises of this diner.
Other questions scrambled my mind: do they pre-make the $1 egg sandwiches? They must. There is no way the diner can meet the short-term, burst demands dictated by the average time one waits for a train.
And what is the optimized inventory of egg sandwiches that minimizes spoilage and maximizes freshness, demand, labor…? The $1 egg sandwich production quickly becomes an n-dimensional optimization problem.
And by “optimization” I mean the mathematical definition: maximizing (or minimizing) some outcome or value within a set of predetermined constraints. A classic example is an investment portfolio: we are all trying to maximize the value of our portfolio subject to the constraints of contributions, time, risk, market direction, etc. But I digress… back to the eggs.
Maybe the $1 egg sandwich starts at $2 earlier in the day and, by the time I arrived, the decision was made to drop price due to surplus inventory. Wouldn’t it be something to find out that a mom & pop diner was using sophisticated optimization algorithms to price egg sandwiches that maximize profit and minimize spoilage?
At this point three things become apparent:
1. Tying strategy to execution is as critical to the mom & pop diner as it is to Global 100 companies;
2. The best decision management solutions must include an optimization component; and,
3. I have an unhealthy obsession with egg sandwiches.
I encourage you to attend the IBM Innovations in Smarter Analytics Virtual Summit (June 19, 2012 at 10:30 am ET) next week when we discuss the importance of business rules, predictive analytics and optimization, and how all three make up our soon-to-released IBM Decision Management solution.
In fact, IBM Decision Management uses a variety of optimization techniques and this is what makes it truly unique in a field of decision service solutions. It rounds out the list of “must haves.”
Along with egg sandwiches.
For more information: Read parts one (rules) and two (analytics) of my Decision Management series of articles.
**”Alice” and “Flo” are copyrights of Warner Bros. Television and Columbia Broadcasting System (CBS)