A compilation and review of articles about technology, current products, and discussion of how it all sometimes has unintended consequences.
Managing Technical Debt
Everyone knows they must manage their financial debt to be successful in business. Managing “Technical Debt” is another matter. Far from an imaginary concept, “tech debt” is real. Almost every project incurs technical debt over time. Typically during the development and production phases. Unrealistic expectations, "scope creep," stakeholder demands, or poor project management can encourage software development teams to sacrifice quality or take shortcuts. While some “tech debt” can speed the development process, unless it is “paid back” with a revision, the longer the debt is allowed to accrue the more difficult and expensive it becomes to fix. Just like financial debt, companies either must address it or ignore it at their own peril. Eventually the “loan comes due.” Steven Rabin writing in the December issue of SD Times presents an excellent case for managing your technical debt. Highly recommended reading.
In business, knowing how we are performing in relation to our competition is vital. Internally we want to know if we are using resources effectively and getting the most out of what we have. Efficiency and Productivity are two calculations that are fundamental to the success of any organization. While the calculations are simple, choosing what measures to use and collecting the necessary data requires a thorough understanding of your industry.
To calculate Efficiency you will have to first decide what to use as a base for comparison. Does your company already have a “target” of some kind? Like total units produced? If so then you can compare everything to that. Once you have that, there are a couple of basic formulas that can be used:
Efficiency = Actual Output/Effective Capacity X 100%
Utilization = Actual Output/Design Capacity X 100%
Design Capacity is the maximum output achieved under ideal conditions. Effective Capacity is always less than Design Capacity because of factors su…
Last week in Operations Management we used Excel to calculate the Economic Order Quantity and graph Carrying Costs, Ordering Costs, and Total Costs.
The Economic Order Quantity or "EOQ" is the order size that "minimizes" Total Costs. Any more or less and you are spending too much on ordering or too much on keeping inventory.
For example, in the Excel spreadsheet below, if you had an Annual Demand of 12000 units, Ordering Costs of $10 per order, and Holding costs of $4 per unit per year, the EOQ would be 245 units and Total Costs would be $980.00:
We used the following formula in Excel to calculate EOQ: =SQRT((2*B2*B3)/B4)
And the following formula to calculate Total Costs at this point: =$B$6/2*$B$4+$B$2/B6*$B$3
To create the graph, we used the following formulas and simply copied them over a range of 100 to 500 units.
Ordering Costs: =$B$2/D2*$B$3
Holding Costs: =D2/2*$B$4
Total Costs: =F2+G2
Looking at this chart, we can clearly see that our order size of 245 is indeed &q…
September 9, 2009 - Today in my Operations Management class, we analyzed customer complaint data for a small grocery chain. Over a nine week period, "Tip Top Markets" had been collecting data on customer complaints. Examples included comments such as: "stale bread," "overcharged," "checkout lines too long," "meat spoiled", "out of 42 oz tide," "eggs cracked," and "store not clean."
Students first tallied the complaints for each week using five categories and entered the data into an Excel spreadsheet:
After calculating total complaints for each category as well as the cumulative percentage, they created a Pareto Diagram and Run Chart as shown:
According to the Pareto Diagram, "Tip Top" has real quality issues in the areas of "Out of Stock Items" and "Service and Maintenance." The Run Chart shows over time how, after implementing a quality improvement program, their stores have…