Protégé

Ran into one of my favorite people this morning whom I hadn’t seen in several years.  Was absolutely wonderful seeing her,  and made me think about the protégé relationship.

Having an amazing protégé must be like having a Padawan,  but more analytics,  less light sabers. (for a good explanation,  see wookiepedia…seriously.  Yeah I couldn’t make that up if I tried)

When your protégé passes you on the ladder to success,  it is such a proud moment. 

I hope she gives back as well. 
 
I have only had a few protégé’s since I graduated from student to teacher,  so to speak,  and I hope they all experience the same levels of success.

Analytics drives business,  but relationships bring it home.

-That Planning Guy

Pricing Analytics in an F&B Environment

I have been thinking more and more about the pricing analytics that we are applying with great success in Retail and how it can be applied to a restaurant environment.   An item sold has similar attributes attached of location, unit, retail, and COGS. Why is it relevant that it’s a store? Couldn’t it just as easily be a restaurant or a bar?  In fact, the cross-brand analytics might even be more compelling.  Isn’t a Bud draft a Bud draft? Or soup a soup? (Varying costs, but like-for-like probably close?)  I will speculate below.

Lets get mathy, my fellow #datanerds!

Say a Miller draft costs $1.00 and sells for $5.00 in your restaurant.  (I made that up, of course. I would hope the cost is lower, but I don’t know so I like a round number.) You are selling 100 per day at this price.

What’s the break point of different elasticity?  How much can we drop units at each price point and grow profit, and hopefully revenue as well?

grop3

 

To me, the safest bet above is the $5.50 test.  The most likely outcome is the scenario #2, which is  .9 elasticity, resulting in a slight revenue pick up, but a 2.4% profit increase.

Couldn’t this apply just as easily to food? My first inclination is to test deserts. But conversely, I am thinking about a lower price to drive units (I know… that’s where my head is too.)  Let’s assume a cannoli costs $2.00 and retails for $7.00.  What scenario and grid would be the likely outcome?

grp33.png

Again, the pricing signal, with all things being true, would point to a $6.00 price test, and likely the middle scenario: +$28 topline, $12 bottom line. And, 8 happier people.

IF.. and it is a big if.. we could raise a beer, and lower a desert, resulting in a higher total check and increase profit, that’s win- win.   Also, higher cover means higher tips, so happier servers. Win-Win-Win.

In the food space, I would be really curious to apply t0 an add-on menu: Adding items to a pizza costs $2.00, adding cheese to a burger is $1.00, adding a side of turkey bacon to breakfast is $4.00 and so on.  I’d love to see how these pencil out in real-time, both up and down.  How elastic are add-ons? Maybe a 3/$5 deal on a pizza? It seems like add-ons are zero ‘overhead’ and are true incremental pick up -minus COGS of course which I suspect are low, considering.  A slice of cheese for a dollar- that has to be 90+margin. These seem like huge margin drivers….Shouldn’t we be maximize units? (and creating the perception of value?)

Once we can apply this to a bigger scale, and have a few thousand data points to determine best outcomes, the math – and break point- should become self-evident. They  likely vary by location, by region, by geography.   And numbers don’t lie.  I imagine in a large-scale F&B environment the math should justify whatever price-management tools are needed.  BWW? Applebees? Chilis?  Even the neighborhood pizza place.

Analytics Drives Business.

-That Planning Guy

PS- A beer and a cannoli for dinner? Hope there is a calzone in between!

Next Speaking Engagement~

Short message tonight…

This week I will be at this event:
https://theinnovationenterprise.com/summits/marketing-analytics-innovation-chicago-2016

Looks to be a great event- very looking forward to it!

And, Chicago is a great place.  Last trip was a lot of fun. And Deep Dish Pizza.

-That Planning Guy

Upcoming Events

A few events to mention this week….
First, this Thursday, 5/12 – a LIVE WebX!
We’ll be talking about one of my favorite topics, PRICING! Hosted by Joe Skorupa from RIS News (@risnewsinsights), the panel includes the amazing Sahir Anand from EKN (@sahiranand, @EKNResearch) and Cheryl Sullivan from Revionics (@Revionics) who know a thing or two about pricing analytics!
Should be a great discussion!

Register here: http://risnews.edgl.com/web-event/5-Critical-Components-of-Advanced-Pricing-Strategy105100?referaltype=revionics

 

Then next week, Road Trip!  LIVE in Chicago! Very excited to participate in a Innovation Enterprise event! Incredible line up of speakers and some just-added compelling panels!
https://theinnovationenterprise.com/summits/marketing-analytics-innovation-chicago-2016

Who’s in?
-That Planning Guy

 

Venn Diagram

This is a weird week for me as so many people are in town for various reasons. 
Makes me think of Venn diagrams.

image

In a classic Venn look at my relationships,  one cirle can be work relations Q1, one is friends&family Q2,  and the 3rd is people I know from work but don’t work with Q3….

Some are easy: buddy I grew up with was in town.   Was great catching up,  meeting his wife.   Q2.
One of my best friends used to be a guy I worked with but he left the company about 5 years ago.   Clearly  Q2.  But sometimes a Q3 as we talk shop about various things on occasion. Q23. 

Some more complicated: guy used to be in Q1,  worked for a company I dealt with.  Now he’s with a different co.  in a different role.   Great time catching up.   Seems like a Q2 now.

Scenario today, current software vendor golf tourney,  lots of cool people,  Q1. Business dealings galore. Great relationships,  but really Q1 based.

I am planning dinner Wednesday (I am Thatplanningguy,  of course planning a dinner!) with buddy from a Research company,  Q3.  

But,  what happens when people move around companies or someone is in a Q for a long time? Do they move to Q2 of my life over time?

Several great folks in town,  some of my absolute favorite(favourite even) people.   If circumstances change at work one way way or another,  I hope they move to Q2.  I would be saddened to lose touch.

The last time I changed jobs I was sure who I would still be close with,  and was wrong on almost every one.  

If  circumstances change the dynamics of your relationships,  who will still be in YOUR circles?

Making them overlap into Q123 might be the best way ‘blend’ your life well in this globally connected life.

Time will tell,  I guess.
But for today,  I am THAT Planning Guy.

Weakest link failure

We spend millions of dollars on systems.  Planning,  Merch,  Analytics tools, registers.

We spend massive efforts developing plans that bring the right product at the right time,  and most recently at the right price. 

Buying spends huge efforts and tremendous talent on selecting the best products,  and getting the best costs.

The distribution center works hard with both technology and people to get the product in,  owned,  processed,  and distributed. 

Accounting pays for it in order to get discounts as well as keep us out of credit hold issues.
The operations team get the goods through the stock rooms onto the floor,  and Visual teams make the displays effective and alluring.

And all of this effort is worthless when the point of contact with the customer-  the sales person- fails to greet,  sell,  close. 
Only as strong as the weakest link. 

Why is the most important link in the retail cycle ‘chain’  so often the least trained,  lowest paid,  entry level person? Critical part,  often overlooked.

Like putting cheap poor tires on the performance car.   All that horsepower,  and it can’t get to the road.

FIX THE PROBLEM

-That Planning Guy

Vacation, and the the Demi-God Maui

Back from vacation. It’s always hard to come back and get into the swing of things, but alas, what makes a vacation special is the time in between them I guess.

Taking a divergence from my usual Greek God commentary to add in a few Legends of Polynesia…

The legend of Maui is one of my favorites: Maui climbed Haleakala and lassoed the sun to make it move  slower and make the Hawaiian day last longer.  As one who enjoys spending a lot of time under the Hawaiian sun, the length of the day is delightful. Sunrise, sunset, and everything in between.
(Maui did several other things, such as creating the islands by hooking the ocean floor and he and his brothers pulling up the islands…)

Sometimes when we think there is not enough time in the day to accomplish all our tasks, we could use a Demi God like Maui to lasso the time clock and slow it down to give us more analytics time in the day. Perhaps we need a god/goddess of Big Data?  ‘Datalist’ should be the God of Big Data and Analysis? Open to other suggestions~~~
In the meantime, tomorrow is Monday morning, the birth of new data to review, and Datalist will be busy.

With much Aloha,
-That Planning Guy

Next speaking engagement

Looking to meet me or see me live? Well then,   buckle up and catch this great event:
Marketing Analytics Innovation Summit.  Should be a great event.

https://theinnovationenterprise.com/summits/marketing-analytics-innovation-chicago-2016?utm_content=buffer4e17d&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer