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IE in IT Horror Stories

In the spirit of Halloween, here are a number of IT horror stories for your enjoyment.

Note: all of these IT horror stories are from my personal experience or observations working with a variety of organizations and clients.

  • “We will pay you $XXX to come down and run this critical report. The only guy who ever ran that report just had a heart attack and we have to have the results. If you can figure out how we can run it some other way ourselves, the price tag is XXX more.”
  • “The low cost software we installed is actually just the framework. You have to pay them to program it with the workflow. That’s extra.” “How much extra?” “More than the cost you paid for the software application in the first place.”
  • “Yes, we can use it for activity based costing, but we have to set up the resources in the application in order to use ABC. And no, the software setup does not include that already.”
  • “I need your help. I spent all day in training, but I don’t know how to log in.”
  • “The testing didn’t include that because we saved time running it through the happy path.” (Testing only included proper workflow and routing, not mistakes people were likely to make.)
  • “I think it will be in the manual. Here’s the manual,” as I was handed a 600 plus page book.
  • “The files are missing.” “Can you restore them from the backup?” “We think they were deleted before the last backup, so they aren’t in the latest backup.”
  • “In response to questions that came up in training, we’ve emailed out a copy of the user guide.” I opened it to see the rough outline I’d written and asked for the trainers to review.
  • “We can’t delay release due to errors found in testing, we can’t afford to delay the release again!”
  • “Can’t you drop more things from the test plan so testing can fit the schedule?”
  • “The guy they assigned to package it has never done this before.”
  • “I did read your tech support documentation on this issue, and it didn’t answer my question.”
  • “We imported the data and found X% have these character issues. Can you create a list of it so we can create a quick clean-up script?”
  • “I’m calling this phone number because your main customer service number only gives me a message to go to your website, but the problem with the website is that it is down.”
  • “This is outlined in the lessons learned in the knowledge database.” “You can’t expect anyone to read that.”
  • “The software release can’t go in that week because the only guy who can do it is taking that month off.”
  • “I have to email you personally, directly, because the general email to the tech support group bounced.”
  • “The user called; the file is there now, but it is upside down and backwards. So how do we fix that?”
  • “Before you refer me to your first level tech support for this issue, let me inform you that I work for tech support here, and this error I’m reporting isn’t for one user – it is for all of them.”


Knowledge capture and redundancy in critical skill sets, adequate planning for tests combined with thorough testing, redundancy in backing up essential data, thorough documentation of technical support accessible to as wide an audience as possible, project planning for IT that includes all necessary steps and multiple channels for reaching appropriate levels of IT support are all necessities to avoid horror stories like these.

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What eBay and Amazon Selling Taught Me about IT Design, Updated

My father was amazed when I told him I found replacement parts for several older appliances in a house we were fixing up for rent and/or sale. I found the replacement part for the dishwasher on eBay and pool pump part on “I thought Amazon only sold books,” he remarked. “And wasn’t eBay where you did a lot of the kids’ Christmas shopping?”
eBay is jokingly referred to as America’s garage sale. Amazon began as a low cost online book store and became the Walmart of the internet, selling everything from baby diapers to Zithromax for fish (and preppers).
These websites are popular because of their offerings. Their selection is driven by ease of use by both customers and sellers. And this in turn is driven by good IT design.

What can the rest of us from the design of these sites, and how can we apply them to our projects?

Simple Setups are Incredibly Valuable

A system that enables someone to step in and set themselves up, ready to go in a few minutes, is invaluable. IT systems based closer to the principles of simple and basic functionality as suggested in “Rework” by Jason Fried are superior to software applications and sites loaded with apps and features that take hours to learn and days to master.
eBay and Amazon are known for their simple setup for new customers, often letting you start selling your products in a matter of minutes. Both sites are the 800 pound gorillas on the internet because they made getting started simple. These sites benefit from millions of sellers reaching consumers through their websites, garnering a portion of the third party sales as well as a wider breadth of products that bring more consumers to their site than the competition’s. This makes the simplicity of the user setup a value added business proposition.


Ensure that Customers Can Find What They Need


Amazon has added an incredible number of sorting criteria to let consumers find the right product based on their criteria. They used crowd-sourcing via Amazon Mturk to winnow product information to identify the key aspects of a product so that consumers have access to the information they need and not much more. The end result is a shopping experience akin to walking into a boutique, asking for what you need and being shown a dozen items sorted by your preferences. eBay, too, has numerous criteria that let consumers search by criteria important to them and related to the product category, aside from simply relying on SEO. The only major changes to the SEO of Amazon’s listings is the addition of FAQ to land conversational queries and the Amazon information appliances that almost default to Amazon’s site.

Whether it is searching through a database, finding help resources or identifying the meaning of an error message, ensure that customers can find what they need when they use your product.

The Right Amount of Information

Insufficient information causes your product to get missed in keyword searches. Too much information causes customers to wonder if your product is the right one. Give enough information to prove that your product is (or isn’t) what they are looking for. Send a technical specification sheet and assembly instructions with the product.

Balance the amount of information consumers get. A lack of information is frustrating, while hitting them with a fire hose of information is overwhelming.
Proper Design Prevents Replication of Errors

A well-thought out website or product design at the onset is the foundation of the endeavor. It is easier to plan out a good design and build it than to set something up and then spend much more time trying to fix it. This is especially true when a system is expanded via replication and federation. If it is a hassle to make changes to one system, try implementing a fix in two or more versions or multiple databases.
IT is revolutionary in many ways because it is so scalable. Hence the joke that a computer lets you make a mistake a thousand times faster and ensure that millions know about it. Proper design prevents replication of errors on a vast scale, so build in robustness, quality, interoperability and ease of use from the onset.

Reputation Matters – and It Matters Most at the Beginning

When a seller starts, the first few shipments establish the reputation. A bad rating early on takes a dozen more five star reviews to offset. A software application with a problem-prone initial release will take months of customer care to make up for the initial problems. It takes more work to make up for a bad first impression than it does to create a good first impression. Your reputation matters, in online selling and service. It matters most in the beginning, because new customers are those most willing and able to leave your products or service agreement.

Focus on quality when designing an IT system or service. Ensure that it meets customer requirements and is bug free. You should wait another month or two to release something instead of making a bad impression that you may never undo.

The Light Hand of Corporate Governance

My father once said the greatest thing America has in its favor is political inertia. A long history of personal freedoms, local decision making and peaceful coexistence keep the country strong despite recent national erosion of our freedoms and bad governance. People can and do rely on a strong collective history and set practices to resolve problems even when the national government seems paralyzed. We can take care of things mostly by ourselves because we have had to in the past, and we have many close at hand solutions to fix things before bringing in the big legal guns.
Both Amazon and eBay utilize a similar inertia to their benefit (and that of customers). The default response to bad service is a bad rating, the second is reporting it to the selling website, and the third is researching the terms and conditions to see what other recourse you have.

Reputation scores and customer ratings warn customers of bad apples quickly, and the threat of a bad review often leads to resolution of service problems without relying on website management getting involved. Well-designed dispute management practices exist on both Amazon and eBay to mediate problems that may have arisen due to third parties, such as shippers. Dispute resolution is focused on helping each side find a solution that they can live with. Heavy measures like banning someone are a last resort, but one that exists. The light hand of corporate governance leads to a better overall experience for everyone.
Design IT services and systems so that system administration doesn’t appear heavy handed or arbitrary. Give consumers multiple avenues of reporting problems and seeking assistance.

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A salary analysis of industrial engineers

By Zubin Ajmera

When I was new to the field of industrial engineering, I had zero idea on what the field was about. What do industrial engineers do? Where do they work? What do they do on a daily basis?

These were the type of questions almost everyone has when they start out. But sometimes the hidden truth behind all those questions is that we want to know the salaries of industrial engineers – how much do they earn, which industries within IE are more lucrative, what’s a good benchmark salary for an IE, etc., to see if this field is worth the academic investment.

So I started doing some basic research and I discovered there is no good resource which can provide valuable information on this topic. And it couldn’t have been a better idea to put this valuable information on the platform of IISE – the hub of industrial engineers.

In this blog, we’re going to talk about salaries of industrial engineers. The good thing is we won’t just talk about salaries, but we will talk about the factors behind them.

Ultimately, a salary boils down to the three most important variables

  1. Experience: Are you a new to the industry or have had experience?
  2. Degree/Education: Have you earned a bachelor’s degree, master’s degree and/or a Ph.D.?
  3. Location: Where are you working? Atlanta, New York, Mumbai, Chicago, Delhi, Seattle, Boston, etc.?

Of course, there are many variables like company size, performance review, interviewing skills, negotiating skills and others, but I consider the three listed above to be the most important in determining your salary.

I narrowed down the best major cities to work in based on a mix of data from reliable sources, references and my experience:

  • Atlanta, New York, Boston, Chicago, Austin, Houston, Los Angeles, San Francisco, Charlotte, Seattle, Detroit, Columbus (Ohio).

I also took in-depth data from since it provides reliable information regarding the actual salaries that industrial engineers are offered. I also factored in my experiences after working in four states for seven different employers as well as interviewing with almost 50 companies.



Let’s begin.

Graph 1: Salary Analysis for Bachelor’s Degree Recipient with Experience by City

Below you see that “x” is the years of experience. Typically:

  • A recent college graduate has less than one year of full-time work experience
  • A mid-level professional has anywhere between one to three years of experience
  • A senior professional has more than three to five years of experience



  • Highest Salary: $82,045
  • Lowest Salary: $59,543
  • Average Salary: $68,980

Graph 2 : Salary Analysis for Master’s Degree Recipient with Experience by City



  • Highest Salary: $83,236
  • Lowest Salary: $60,348
  • Average Salary: $69,847

Graph 3: Salary Analysis for Ph.D. or Advanced Degree Recipient with Experience by City



  • Highest Salary: $84,535
  • Lowest Salary: $61,233
  • Average Salary: $70,880

Key Takeaways :

  • Salaries lie between $60,000 per year to $70,000 per year: Almost all of the salaries fit in this range. When I started my career, 1) I never found a good resource to rely upon; and 2) The answers varied from $60,000 per year to $80,000 per year, and even $100,000 per year. But now you have a good benchmark by which you can compare.
  • Not all salaries will encompass the industrial engineering spectrum: As we know, the field of industrial engineering is broad. There are positions in supply chain, manufacturing, consulting, data analytics and more. What we have done in this blog is captured a bird’s eye view for the position of industrial engineering so we get a good idea for all of its domains.
  • Most high earning salaries come from the U.S. west coast: This is for obvious reasons and true for any major or job, so don’t confuse this when you do your math.
  • Your navigation map: Finally, take this analysis as your navigation map and not the final answer. At the end of the day your salary will be affected by many factors. Also, these numbers may change over time, but for the immediate future, you can refer back here and review to get a good benchmark to help you find the right job that pays well and starts your career.

About the Author

Zubin has a master’s degree in industrial engineering and currently works for a logistics company. He has experience in multiple roles among manufacturing, consulting, and data analytics. He aims to help aspiring industrial engineers in their career endeavors.


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Supply Chain Analytics offer big improvements to Lockheed Martin Aeronautics Company

ATTN: Business and company leaders whom aspire to excel,

Meet Drew Harnish, P.E. (B.S. and M.S., industrial and systems engineering, Oklahoma University), senior project engineer, Lockheed Martin


There are tens of thousands of unique parts that are assembled to make the F-35 Joint Strike Fighter and dozens of locations across the globe that require shipments of parts. The bulk of the part consumption remains at production sites but as more jets are delivered to our customers, there is increased demand for spares and upgrades at military bases around the world. The part demand requirements and associated supply replenishments are captured in our Material Requirements Planning (MRP) system which allows analysts and buyers to see tabular snapshots of real time demand and supply for any given site at any time. As our production rate begins to ramp to triple the current rate and more F-35 bases are stood up, it has become an increasingly manual task to make decisions on supply allocations when challenges arise.

Consider this scenario: a fielded jet is grounded in Arizona due to a damaged part and the base requests a spare to be delivered ASAP. An items analyst sees this request, notices a part available in the Texas warehouse that hasn’t been allocated to an aircraft, requests a transfer, and solves the problem. The base is happy. Easy, right? Next, a production buyer receives a notification that there is not enough supply on hand to meet discrete demand in the factory. The buyer is confused because there was enough on order and there have been no scraps on the line. The reallocation results in a part shortage on the production line, increased labor cost to work around it, and increased material cost to expedite a single part which had already been purchased as part of a block buy. Program management blames production, production blames supply chain management, supply chain management blames sustainment, and everyone is really doing their best to deliver for their customer. There are countless shortage meetings to heroically solve problems just like this on a daily basis. They all stem from the same two root causes; there is no single source of total aggregate part demand or a model to account for quantity risk from unplanned part demand. This happens to a lesser extent when parts are scrapped on the production line with no safety stock in place but is exacerbated when multiple locations introduce unplanned demand into the supply chain community.


In 2014, Lockheed Martin Aeronautics Company stood up an Enterprise Integration team. This team combines the use of advanced analytics and predictive modeling capabilities with operational excellence skillsets to solve systemic problems that cut across functions. One of the first projects our team led was a multi-pronged demand and supply planning optimization effort that eventually resulted in the creation of a new organization with new capabilities. As one of five project leads, I was responsible for leading the team that developed standard business rules for solving demand/supply problems like the scenario discussed above using newly developed predictive analytics. The primary analytics model was an integrated risk-adjusted demand requirements model referred to as “Big D.” This tool aggregates all of the discrete part demand data from our MRP systems and stacks a risk-based order quantity (RBOQ) factor on top which is modeled from historical experience such as scrap, repair, unplanned field demand, and other less-than-lead-time demand. The integration of this data with the risk models allows Big D to plot two critical visuals: 1) a month-over-month demand profile from all sources including overall risk for each part which allows the user to identify parts needing stop-gaps such as safety stock before long term fixes can be put into place, and 2) a month-over-month supply profile that shows discrete and risk-adjusted line of balance (netting of supply vs. demand) to highlight areas where MRP shows healthy supply plans but the risk model indicates high potential for problems.

For three pilot areas, we analyzed the line of balance 60 days outside lead time for over 100 unique part numbers. Using the data from Big D, we developed a decision tree to triage each part based on its risk factors in order to categorize short and long term solutions for recurring issues. The methods we developed formed the basis for a new supply plan health analyst role in the company that did not previously exist. There are now multiple analysts dedicated to analyzing part issues just outside lead time to mitigate shortage risks before problems occur. This has resulted in an increase in collaboration between our production, sustainment, and supply chain teams.

The overall project team responsible for leading this enterprise transformation was over 70 people from all facets of the business and a number of consultants. The specific team discussed in this case study was made up of 16 people from Lockheed Martin and Deloitte Consulting, 5 of which were industrial engineers.”

Industrial and System Engineers provide incredible value to any organization in any industry and I am really excited to share these stories and inspire you and your company to hire ISE’s.

Blessings to you all!

Best Regards,
Michael Foss
President, Institute of Industrial and Systems Engineering