Storify – #ChicagoHCM: ADP’s Regional Open House 2014

For those that check out my blog from time to time, if you click HERE on this link, it will take you to a Storify I created to chronicle the 2014 ADP Regional Open House.

The theme was Social – Mobile – Global, it was a great success with hundreds of clients in attendance.  Seminars, Demos, Free Food and Drink all Day…hopefully we will see you next year.



We offer 3 Kinds of Service: Good – Cheap – Fast…you can pick any two (things to consider)

I had first seen this sign taped above the computer of an IT guy about 15 years ago.

Like all great jokes or social commentary, there is a lot of truth in this statement.

Below is a simple example to illustrate my point, and 3 things to consider before picking:

Three kinds of service.jpg

Having spent most of my career in professional services industries, I can think of countless examples of how this is true…but lets make this a little more relevant by associating it with something we have all experienced: going to the Car Wash.

Good Service (wash) Cheap –> won’t be Fast.  They are going to do a good job, it won’t cost a whole lot, but if they get backed up because of using cheaper technology or are understaffed, you will need to wait until they get to you.  Moreover, since you are not paying much, employees might not be breaking their back to work quickly.  This is okay, just know what you want, and be prepared to deal with the manner in which you get it.

Good Service (wash) Fast –> won’t be Cheap. They are going to do a good job, and it will be fast, but you are going to need to pay for it.  This company is probably heavy on staff, using top-notch technology, and they hustle. They might even check your tires and top off your fluids. However, plenty of good employees and good technology are not cheap, you need to attract better staff with better pay and/or benefits, you need to invest in the best technology, and as a result you get to have your cake and eat it to…it’ll just be expensive cake.

Fast Service (wash) Cheap –> won’t be Good.  Here we have the speed of Example 2, but we are using the staff and technology of Example 1.  Your car will get washed quickly, and you won’t pay much…and that is okay.  Maybe you just need the visible dirt or road salt quickly washed off.  But don’t be surprised if there are some streaks on your windows, or if they miss a few spot.  After all, you got what you paid for.

Enough of the overly simplified and strained analogy…the point here is this:

  • You must include the Expectations you have for Delivery/Execution of any business transaction included in the scope of your project/purchase.
  • You must include the Perceived Value and Tolerable Related Cost of how you will receive your Purchase in your List of Expectations
  • Be sure you understand your options, we make these subconscious-judgments every day when we decide to go home and eat, or stop at a Restaurant, or drive through a fast food establishment.  Before making a decision, ask how Fast, Good or Cheap will impact your Experience; you may be willing to live with the result, or you may be willing to pay for a better one.

Demystify Big Data – Great Video Series

I am not an engineer, nor am I a “data scientist.”  But, I am in business, and I do have a passion for Operations & Finance.  The ability to leverage Big Data, successfully query the data set, and extrapolate impactful conclusions has transformed decision-making in business.  A trend which will only intensify.

When I was looking to conceptually get my arms around Big Data, I found this video series very helpful. Here are 6 short video clips from Christophe Bisciglia, founder of Cloudera and former Google star.  This is probably the simplest explanation of Big Data for someone who is starting from scratch.

Click on any of these links below to watch short video clips per the title:

Hadoop and Big Data 1 of 6 – Challenging Old Assumptions

Hadoop and Big Data 2 of 6 – Processing Petabytes

Hadoop and Big Data 3 of 6 – Technical Overview

Hadoop and Big Data 4 of 6 – One Data System with Many Users

Hadoop and Big Data 5 of 6 – Ferrari vs Freight Train

Hadoop and Big Data 6 of 6 – Augmenting Existing Systems