How not to set your IT budget

If you have read my posts in the past, you will know that I advocate the use of the following formula for determining the ROI for any given improvement project (whether IT-related or not):

Where

• ROI = Return on Investment
• delta-T = Change in Throughput, and Throughput is defined as Revenues less Truly Variable Costs (TVC)
• delta-OE = Change in Operating Expenses
• delta-I = Change in Investment

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Incidentally, where there is no change in I (Investment, including changes in inventory) or the change in I is negative, then projects can be compared based on profit alone. That formula is simply:

Profit = delta-T – delta-OE.

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However, here’s what far too many IT project’s ROI calculations look like:

ROI (don’t know) = ((never took time to estimate it) – (never took time to calculate it)) / $200,000

 

The only figure the company knows going into the project is the estimated “investment” or “cost” of the project.

The common excuse

The common excuse for not calculating an ROI for an improvement project is that changes in Throughput and changes in Operating Expenses are “too hard to estimate,” and “if they are estimated, they will be wrong anyway.”

This argument is specious on the face of it. Think about it!
The $200,000 estimated “cost” or “investment” value of the project is likely to be wrong, too. But that does not keep the CIO and CFO from making their best efforts to calculate that value.

The Real Reason

Of course, the real reasons that CIOs and CFOs do not take time to calculate a real and measurable ROI for their IT (and other) improvement projects is likely two-fold:

1. Too many CFOs and CIOs are under the wrongheaded impression that the value of IT (or other improvements) is both “automatic” and “cannot be measured.” When it comes to new technologies they have succumbed to the strange notion that new technologies are like an engine additive for business—you just pour them in and somehow your business will run smoother, faster, longer and get higher mileage! And, just like people who buy engine additives, they never take time to calculate whether there was any real benefit from using the product.
   
2. They have never taken time to actually determine what root-cause they are attacking with the IT (or other) improvement project, so they do not really know whether the project will actually lead to increased Throughput or will, in fact, drive down or hold the line on Operating Expenses. In fact, they probably do not even know what the “weakest link” is in their customer-to-cash stream or whether that weakest link is internal to their organization or whether it lies somewhere outside their organization in their supply chain.

Isn’t it time to stop that kind of folly? Can businesses still expect to thrive and grow without taking a sound look at how and why they are spending their most valuable resources—time, energy and money?

I don’t think so.

Dynamic Buffer Management (DBM) for the Supply Chain

Dynamic Buffer Management (DBM) for Inventory and the Supply Chain on Prezi

Here is the presentation I made to the RKL eSolutions ERP User Group in Lancaster, PA, on Friday, 11 May 2012. Please contact me directly via the link below if you would like a copy of the accompanying white paper, as well.

Misleading allocations and how to fix it–Part 2

[This is a continuation that will make very little sense to you if you don’t go back to read Part 1. Sorry.]

ACTIVITY-BASED COSTING ALLOCATIONS

Well, the partners were disappointed with these results, for sure. So, they decide to try Activity-Based Costing (or ABC) allocations. The administrative overhead is allocated based on their analysis of the amount of activity that the partners must undertake with each job type.

The ABC allocation of non-administrative overhead was done based on production-hours ($9,000 divided by 1,000 hours = $9.00 per production-hour).

The results of the partners’ new calculations (based on the historical product mix) are shown in below where you will note that company profit remains the same ($4,100 per month).

However, new priorities emerge: now the most profitable jobs appear to be landscaping (at $35 per job) and gutter guards (at $28 per job).

Based on these data, the partners rearrange priorities to allocate resources (i.e., the 1,000 hours or production time available) to capture the available markets for these job-types first. The results of this change in priorities may be seen in the following table:

Like the previous example, at first things look good: “calculated profits” boost to $7,924, but after subtracting overhead not absorbed (by abandoned job-types), the results are disappointing. Only $1,300 per month in net profits.

HOW TO FIX IT: THROUGHPUT ACCOUNTING VIEW

Throughput accounting eliminates all allocations except those that are truly variable with the changes in revenue. Typically, those costs are things like raw materials, commissions (maybe), outside processing costs, piece-rate labor—but not much else.

When you look at these Throughput Calculations, you will see two critical factors:

1. Throughput per Job (Revenues less Truly Variable Costs or TVCs)
2. Throughput per Constraint-Hour (Throughput divided by the time used on the constraint—in this case, the 1,000 hours of production time from the workers is the constraint to making more money)

So, looking at the Current Business and Profitability, you will see that another column as been added that represents the company as a whole or “the system.” Throughput is totaled across the enterprise into this column and then operating expenses are deducted from Throughput.

“Direct Labor” is not included in TVC and is included in Operating Expenses. Why?

Because in most organizations, so-called direct labor is not a TVC. Many times the payroll expense for labor will be the same whether the firm produces 10,000, 12,000, or 8,000 widgets in a month. Not to mention the fact that the payroll for “direct labor” (falsely so-called) sometimes includes payments for PTO, training or other non-productive time.

Note, again, that using Throughput Accounting, we still get the same net profit calculations ($4,100 per month).

Now, with this new information in-hand, the partners decide to prioritize sales and production to capture the market in order by T/C-Hr (Throughput per Constraint-Hour) until they run out of constraint-hours (i.e., the 1,000 hours available to them each month). The results of these new priorities are shown in the table below marked as Revised by Throughput per Constraint-Hour.

Wow! Profits are boosted 230 percent—to $9,410 per month or $112,920 annually—after fully covering all of “the system’s” overhead. In this case, they sought out and captured the 250 plumbing jobs available to them in the market as a top priority. Their second priority was to capture the 145 gutter guard jobs available to them. They had a few of the 1,000 hours left, so they were able to also do 16 window cleaning jobs.

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Hopefully, this helps you see two things:

1. The inherent dangers in believing data coming from an ERP manufacturing (or project accounting) system where the profit figures are clouded by allocations of overhead.
2. The simplicity and clarity provided by looking at your clients’ organizations as “a system” and helping them view their goal as optimizing the entire “system,” not trying to make decisions based on data that may imperfectly represent “system” performance.

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Let me know if this is valuable to you. Thanks.

Misleading allocations and how to fix it–Part 1

Two things about which I warn my clients who buy manufacturing software are these:

1. Manufacturing software is capable of capturing, storing and reporting on reams of data
2. If you are not careful, you will find yourself taking “as fact” the data produced by the system and being mislead in your decision-making

Why is this so?

Because ERP systems allow the users to create allocations of overhead based on manufacturing “drivers.” In Sage 500 ERP’s case (as shown in the screen image below), the chosen driver is “labor hours”—for run time and set-up time.

In the Sage 500 ERP Set Up Work Center screen there are places for “Fixed Setup” costs and “Fixed Run” costs. The values placed here are used to absorb “Fixed” overhead costs at the rate supplied based on each hour of “Setup” or “Run” time calculated for production utilization of the Work Center.

The problem is that these “absorption rates” must be calculated based on historical (or prognosticated based on expected future) utilization rates of each Work Center. These calculations must make assumptions about product mix, work center utilization rates and operating expense levels. As soon as any of the these factors change

• Product mix
• Work center utilization rates
• Overhead expenses

The data supplied by the calculations will be wrong.

And, since either the product mix or the total of operating expenses will certainly be different than the numbers used in the calculations, the data resulting from the calculations will (virtually) always be wrong.

A simplified example

We are going to look at two different allocation methods and the decisions that might be derived from such calculations.

• Standard overhead allocations by Job (equivalent to allocation per work order in a manufacturing operation)
• Activity-Based Costing (ABC) allocation based on production hours

In order to make the allocations easy to follow, you will see that the company is a service company and that the firm has three partners (administrative overhead) and some relatively fixed overhead in the form of vehicle leases, maintenance and so forth.

The direct labor (production labor) comes from five employees who—to make it simple—all work exactly 200 hours per month and all make exactly the same rate—$10 per hour. This also gives “production” a known capacity—1,000 hours per month.

The partners have kept good track of their history over the last six months and have also done enough market research to have a good handle on the size of the market they are serving. They know, therefore, how many of each kind of job they have done each month (on average), as well as the market potential for the kinds of jobs they do.

STANDARD COST ALLOCATIONS (by Job)

In an attempt to leverage what they have learned by capturing data about past performance and, of course, to improve profitability, the partners do an analysis that includes a standard allocation of overhead to each job.

From this analysis, they discover that their most profitable jobs are landscaping jobs ($35 per job), followed closely by window cleaning jobs ($30 per job). So, they decide to satisfy the market demand in that order, using the resources they have (1,000 hours of production time).

Before we move on, note that with their present product mix, the company is producing a profit of $4,100 per month ($49,200 per year).

The results of this action are shown here:

Upon first glance, it appears that this has been a great move. Based on the calculations in the table, profit has moved from $4,100 per month to $7,200 per month!

Again, the problem is that since NO plumbing or gutter guard jobs were done, some of the overhead (allocated at $90 per job) was not absorbed in the calculations. The total overhead is $18,000 plus $9,000, or $27,000. But the 220 jobs only absorbed 220 times $90, or $19,800 in overhead. That leaves $7,200 in overhead NOT absorbed. Take that $7,200 away from the calculated profit of $7,200 and the company is actually worse off (zero profit) after having reallocated its resources to what appeared to be the “most profitable jobs.”

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[To be continued—be sure to watch for Part 2!]