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I don't post here much any longer. If you want to read more like you've found here, however, you can find me at RKL eSolutions blog or at the Kinaxis Supply Chain Expert Community.

I'll look forward to seeing you there!

Thanks!

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!]

Bad policies hurt the supply chain

I think just about everyone involved with understanding and managing supply chains agree that the supply chain works best when volatility is minimized. Some organizations go to great pain and expense trying to figure out ways to manage their supply chain when faced with sudden demand changes and volatility.

Nevertheless, many supply chain participants continue to maintain policies that actually increase volatility in their own supply chains. Here are some examples:

1. Short-term promotional pricing
2. Volume discounts linked to shipment batches
3. Period-end promotions
4. Salesperson incentives linked to period-end dates

Short-term promotional pricing

Short-term price promotions contribute to the bullwhip effect and create tremendous inefficiencies all up and down the supply chain. The policy—especially when repeated with some frequency—causes buyers to hoard product. They buy extra-large batches of product when “on sale,” and store it up against the days when the product is not “on sale.”

Some short-term promotions are so predictable that buyers actually delay purchases at regular prices knowing that, if they wait, they can buy at a lower price later.

By the time all of the costs and expenses to the supply chain are added up, it would be difficult—in most cases—to prove that short-term promotional pricing actually adds to the bottom line at all. In fact, studies by some firms specializing in creating and managing pricing mechanisms have shown that consistent pricing at a marginally lower level actually produces more sales and profits than higher prices accompanied by short-term promotions.

Consider a brand like Wal-Mart. This is a firm that has master-crafted its supply chain and built its reputation on consistently lower prices. By doing so, it has—over the last several decades—supplanted previously known giants in the retail industry such as Sears, Penney’s, Kmart and more. Yet, Wal-Mart is not known for “sales” (i.e., short-term promotions). It is known for its consistently lower prices.

Volume Discounts linked to shipment batches

Let me say, off the bat, that there is nothing wrong with volume discounts, per se. The problem is linking volume discounts to transfer batches. In order to realize volume discounts without causing supply chain hoarding and needless volatility, the volume discounts should be separated from the shipment batch.

For example, your customer might get a volume discount if they agree to buy 100,000 units next year, but you might agree to transfer them to them in relatively equal weekly or monthly shipments. This evens out production (on the supply end), warehousing (on the receiving end), and doesn’t make it look like someone sold 50,000 units in March and another 50,000 units in September with little or no activity between.

Period-End Promotions and Salesperson Incentives linked to Period-End Dates

These two are frequently related. Salespeople with the need to reach certain goals for end-of-quarter or end-of-year sales, in order to boost their commissions, begin a big push. This push is usually accompanied by some authority to also offer special discounts.

All up and down the supply chain, prices are being discounted, volatility is being recklessly increased, and, all the while, production lines and warehouses are increasing their operating expenses to meet the boost in demand. Overtime and extra staffing costs are eating up the lion’s share of the profits that might otherwise have been generated if volatility had been reduced, rather than increased, by rational policies.

 

Of course, there are other wrong-headed policies that needlessly lead to higher volatility in our supply chains, but these are a few that come to mind. These are things well within the span of control of executives and managers where corrective action is easy and at little or no cost. It just take rethinking the way we do business and not being afraid to gore some existing “sacred cows.”

Understanding the “chain” in supply chain management

After 30 years of growth and development, I am not at all certain that I would rename “supply chain management” to anything else. What I might try to do is to get people to recognize the real implications of the name it already has.

Let's look at that key middle word in the name: "chain."

Very few organization "manage" the supply chain as a "chain."

A great many managers and executives are content to manage only their "link" in the chain. If things don't go well, they may try to substitute one connected link for another (e.g., change vendors or find new customers, for example). But they do not recognize or manage the chain as a chain. They still manage pretty much within the four walls of their own "link" (i.e., company).

The important thing to understand about a "chain" is the interdependence of the links and that the strength of the entire chain is governed entirely by the strength of the weakest link in the chain.

The interdependence of a chain should drive organizations inexorably toward supply chain collaboration and, even further, toward a genuine mutuality. In many cases, the fastest, best and most secure way for organizations to improve their own profitability is to work together with other supply chain participants to strengthen the weakest link in the chain—not seeking to replace that link. That means that all the participants in the supply chain—or at least the strategic links—must be (or become) open to collaboration and even invite new ideas from other participants in the chain.

Collaboration and end-to-end data sharing can help end the damaging effects of "the bullwhip," help firms in the supply chain break their frequently misguided addiction to large batch sizes, and help redefine purchasing and pricing metrics that can lead to more frequent replenishment while holding both truly variable costs and operating expenses low for all the participants.

High-level meetings should be sought between executives and managers for all the critical players in the supply chain. The healthiest supply chains are those where all the participants are making satisfactory profits and a few strong players in the supply chain are not using their leverage to increase profits through policies that weaken other important links in the chain.

How can you tell when your "supply chain management" team is beginning to act like they are part of a "chain" and not just content to manage their own "link"? Look for the following signs:

1. Metrics and actions taken for improvement reach outside "our link" and efforts are made to optimize the "whole chain" by identifying and seeking to strengthen the weakest link.
2. Management up and down the supply chain have learned to not ignore the industry's larger ecosystem. They monitor the ecosystem for signs of impending change, manage proactively, and share information freely.
3. Supply chain managers recognize that there will always be a "weakest link" and, while seeking to strengthen the present "weakest link," learn to pace the flow of products by the "drum" of the present "weakest link." They also recognize that any loss of productivity at the present "weakest link" is productivity lost to the whole supply chain. (As a corollary, supply chain managers should recognize that time, energy and money spent strengthening links other than the present "weakest link" will not improve the performance of the "chain.")
4. Managers and executives involved in the supply chain have ceased using metrics stuck in "cost-world" thinking and have seen that it is synchronizing product flow and increasing throughput that lead to ongoing improvement and higher profits.
5. Supply chain managers have recognized that profits depend upon meeting customers' needs and demands, and that understanding these needs and demands is essential from product design forward through all the processes and links in the supply chain.
6. Collaboration across the supply chain begins with product design so that maximum external variety (end-products) can be achieved with minimal internal variety (raw materials, components and subassemblies).
7. Supply chain collaboration is leading to strategic flexibility in both products and the processes of maintaining supply chain flows.
8. Wherever possible, all along the supply chain, the flow of product is buffered with capacity rather than inventory. (Supply chain partners may make strategic capital investments in other parts of the supply chain to build needed capacities as part of the collaboration.)
9. Managers and executives involved in the supply chain have made it a priority to develop strategic alliances and partnerships all along the supply chain in order to recognize and strengthen the present "weakest link."
10. All across the supply chain, metrics focus on increasing throughput (not cutting costs).
11. Forecasts are still used for planning, but "pull" is used to drive all execution in the supply chain.
12. The focus is now on synchronizing the flow of product across the supply chain, not on balancing supply chain capacities.

ONE ADDITIONAL NOTE:

On the contrary side, some "big dogs" (or "big dog" wannabees) in the supply chain think they are managing "the chain," but they treat it more like a "leash." They yank their smaller suppliers around until their suppliers are either driven out of business or simply won't do business with the "big dogs" at all any more.

This kind of attitude is bad for business and bad for the economy in general. The best suppliers are profitable suppliers. If any organization is destroying the supply chain's profitability one link at a time, it is destroying its supply chain by weakening one link after another. These weak links will not have reserve capacities to respond to changes in demand or make up for supply chain losses when "Murphy" strikes.

P.S. - I was going to write on the other words (i.e., "supply" and "management"), but this is probably enough for now. Thanks.

Increased supply chain confidence through simplicity

Traditional approaches to inventory management and replenishment divide inventory stocks into two portions:

1. Working stock – the inventories designed to cover daily demand
   
2. Safety stock – the inventory quantities designed to cover variation in supply or demand or both
   

Years of statistical analytics and software development have been focused on improving the ways in which lead-time, demand and safety stock values are calculated. So much, in fact, that most of the people who use supply chain management, inventory management, or replenishment software frequently do not even understand what the software is doing, how it is doing it, or why it works or does not work.

Some years ago I was consulting a firm and, in the course of the business, reviewing how they went about their inventory management and replenishment. They had software that did inventory management and that included replenishment calculations.

So, we were sitting together and he was describing to me what he was doing on his computer. He said, “Here’s the ordering screen. It shows historical demand here [pointing], and the recommended order quantity here [again, pointing]. And, I don’t know exactly what this number is for [pointing], but if I think the system is suggesting that I buy too much or two little, I can adjust this number until the suggested order quantity lines up with what I think it ought to be.”

Well, of course, what the system was doing was exponential-smoothing of demand and the value he was adjusting was the value of alpha in the formula.

What I refrained from asking him (only by biting my tongue) was, “If you are going to simply adjust the system’s findings to your intuition, why use the system at all?”

The moral is: Systems that are not understood—and most complex systems are not understood—are also not trusted. Especially if they frequently—or even, regularly—produce what are perceived to be unreliable results.

The artificial divide

The artificial subdividing of stock quantities into “working stock” versus “safety stock,” and adding complexities around the factors used to calculate the one value versus the other provides no added value. In fact, the complexity actually leads to less reliability because the users frequently do not know how to set the input parameters effectively. Not to mention the fact that the parameters that are effective today may not—in fact, likely will not—be effective tomorrow or next week.

The fact of the matter is, in most cases, the only awareness of the division between “working stock” and “safety stock” quantities is found in the software itself and those that may be intimately acquainted with the software and its configuration. The people on the warehouse floor typically do not know when they have made an incursion into “safety stock.” They don’t know that the first 41 units they picked for order number 8789089 were from “working stock,” and the last nine units were taken from “safety stock.” And, they should not care.

Even the managers frequently have no visual signal that an incursion has been made into “safety stock.”

Inherent simplicity

Employing Theory of Constraints (ToC) Dynamic Buffer Management (DBM) makes life easier to understand for those responsible for inventory management and replenishment (read: supply chain managers). The buffer size (for any given item in any given stocking location) is a single number. (Let’s say, 1,000 units.)

The formula for setting the initial buffer size is simple and easily understood. Typically that formula is something like this:

Initial Buffer Qty = [Average Daily Demand] * [ToC Replenishment Days] * [2] * [Paranoia Factor]

The only factor that really needs any kind of explanation is the “Paranoia Factor.” This is merely a multiplier selected by intuition and based on senses of the criticality of an item. An item might be critical because it is used in the production of 800 other items; or because the majority of your customers all buy this item; or because one hugely important customer relies upon you for this item; or dozens of other reasons.

Once the initial buffer size has been calculated and set, the buffer is divided (mathematically) into three “zones.” The top third is called the green zone, the middle third is called the yellow zone, and the bottom third is called the red zone.

Going forward, the DBM system simply monitors for conditions at each replenishment cycle and adjusts the buffer size according to rules. The rules are typically:

1. Too Much Green – The item has been found in the green zone on three consecutive replenishment cycles; therefore, reduce the buffer size by one-third.
   
2. Too Much Red – The item has been found in the red zone on two consecutive replenishment cycles; therefore, increase the buffer size by one-third.

It’s that simple. No complex formulas for calculating and managing variability in demand or supply.

On top of that, supply chain managers can have simple visual signals as to the status of their buffers. A simple view of the inventory data (by location) can readily provide red light, yellow light, and green light indicators for the buffer status in any stocking location for any item. No math and easy to equate to action:

• Green light – no action required
• Yellow light – take note, perhaps investigate critical factors like larger-than-normal orders or orders pending for critical customers
• Red light – consider expediting measures, if necessary

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NOTE: There are more options available with DBM, such as identifying and managing SDCs (sudden demand change items—like seasonality), managing Virtual Buffers (between stocking locations, such as warehouse-to-warehouse replenishment, or broader supply chain visibility and collaboration). It is not the intent of this article to exhaust the applicability of DBM.

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RKL eSolutions, LLC is in the process building a cloud-based solution to help you manage your inventory in just such a way—using Dynamic Buffer Management and the Theory of Constraints. Contact me or fill out the contact form here if you would like more information.

The biggest supply chain management mistake over the last 30 years?

I would have to say that the biggest mistake made in SCM over the last 30 (or more) years is the industry’s reliance upon forecasting.

1. Forecasts are virtually always wrong. They may be wrong by a little bit, or they may be wrong by a lot. But they are--for all practical purposes--always wrong. The forecast may be wrong and you have too much inventory--which your firm may call "good' ("Great job! We didn't have an out-of-stock.") or it may call it "bad" ("Hey! Wake up! We are holding too much inventory!"). The forecast may also be wrong and you have too little inventory, which (again) management may call either "good" ("Great job! We sold out of that!") or "bad" ("Hey! Wake up! We lost sales on that because we ran out of stock!").
2. Forecasts only lead to one of two conditions: over-stocks and out-of-stocks.
3. Forecasts offer no assurances of being responsive to the market.

Personally, I believe that if the industry had spent as much time, effort and money on increasing replenishment frequency (reducing lead-time), improving supply chain visibility (end-to-end), making inventory management more agile (providing rapid response to changes in end-user demand) and better understanding and management of sudden demand changes (seasonality and similar events) there'd be a more sales, lower prices, reduced obsolescence and happier supply chain managers everywhere today.

Replenishment frequency

Both Lean and Theory of Constraints management have certainly taught us that replenishment cycles should be as short as possible. One-for-one replenishment is ideal. But short of that, daily is better than weekly; weekly is better than every two weeks; and so forth. When the costs of obsolescence, lost sales, lost customers (due to lost sales), marketing costs required to recover for lost customers, and the many other costs associated with out-of-stocks (on the most popular times) and over-stocks (on the "dogs") if find it hard to believe that most organizations would not perform better with more agile suppliers and logistics even if the so-called "cost of goods" might be marginally higher. Correct valuation of Throughput certainly should teach us that lesson in many, many cases.

End-to-end supply chain visibility

One of the things wrong with today's supply chain is that the manufacturers actually believe that they have made a "sale" when then they sell the product to the distributor. In turn, the distributors believe that they have made a sale when they unload some product on a wholesaler--and so forth on down the supply chain.

The truth is, until the end-user has made a purchase, all the other "sales" have simply put inventory into the supply chain. Inventory that will become obsolete or eat demand for newly-introduced products when liquidated at "discounted" prices. Either way, it's bad for profits in the supply chain.

Imagine how much better it would be if the manufacture (in Malaysia, or wherever) knew within 24 hours precisely how many finished goods were being purchased by end-users every single day. They would know how to pace their production and manage their inventory buffers--as would everyone else in the supply chain!

Inventory management agility

Instead of setting inventory policy once a year, or even several times a year, systems should dynamically adjust for changes in demand (via supply chain visibility) constantly. And, instead of complexity and hard-to-understand formulas, inventory managers should be able to respond to simple visual signals indicating the condition of inventory in their direct control--as well as signals coming from across the supply chain.

Managing sudden demand changes

Supply chain systems should be able to rapidly analyze historical data and identify SDC (sudden demand change) items by simple rules. The systems should then help the supply chain managers understand how to manage build-ups and build-downs for SDC items based on the supply chain production capacities for each item or group of items.

Personally, I think time, energy and money spent in these areas--some of which is now happening--would do a "world" of good (pun intended).

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What do you think?

Sage ERP X3 becomes Oracle Database Ready

Business software vendor, Sage Business Solutions’ ERP X3 solution has been granted Oracle Database Ready status through the Oracle Partner Network (OPN).

The announcement means that Sage has tested and supports ERP X3 on Oracle Database 11g Release 2, and at extension, Oracle Database Appliance. Results demonstrated smooth installation of ERP X3 application databases on Database Appliance.

The Oracle Database 11g Release 2 offers Sage industry leading performance, reliability, and scalability to power business critical applications.

Customer benefits of the solution are cost-effectiveness by lowering storage usage, reduced administration tasks, and enabling consolidation onto secure private database cloud environments.

Sage ERP X3 V6.3 is available on Oracle Database 11g Release 2.

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As reported at ARNet.

Consider the possibilities (especially now, in these challenging times)

A recent survey of published results by manufacturing and service companies[1] that have applied constraint management methods effectively shows:

• A mean reduction in lead time of 70%
• A mean reduction in manufacturing cycle times of 65%
• A mean improvement in due-date performance of 44%
• Mean inventory reductions of 49%
• A mean combined financial improvement (revenue, throughput, profit) of 76%

[1] Mabin, Victoria J. and Steven J. Balderstone, The World of the Theory of Constraints: A Review of the International Literature, St. Lucie Press, Boca Raton, FL, 2000

[Excerpt from Schragenheim, Eli and H. William Dettmer, Manufacturing at Warp Speed – Optimizing Supply Chain Financial Performance, St. Lucie Press, Boca Raton, FL, 2001]

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If you would like help getting started with apply constrain management to your business for rapid ROI and ongoing improvement, please contact me. Find me on LinkedIn.

What’s wrong with EOQ?

Economic Order Quantity (EOQ) EOQ is essentially an accounting formula that determines the point at which the combination of replenishment costs and inventory carrying costs are the least. The goal being to minimize both the ongoing costs of carrying inventory and the expenses involved with replenishing inventory.

The basic EOQ formula looks like this:

As you can see, this formula attempts to balance (simultaneously) the following factors related to the business expense linked to holding and replenishing inventory:

1. Usage rates – how many are sold or consumed over a period of time (one year in the basic formula)
2. Cost of replenishment – how much it costs the firm to replenish a single inventory item (SKU) from the point of recognizing the need for replenishment through putting the quantities back on the shelf
3. Carrying costs – all of the costs and expenses related to storing and handling of the inventory quantities held

Let us take a look at how these factors interact in a practical example:

In our example, we have an item that has a cost of $25 per unit, and the average daily demand is five (5) units. For this firm, the cost of replenishment is slightly above average—sitting at $30 per PO line processed for inventoried goods.

Observe what happens to the EOQ on this item as the cost of carrying inventory moves through the range from five percent (5%) to 40 percent.

When inventory carrying costs are very low compared to the cost of replenishment (five percent and $30, respectively), EOQ recommends big orders. In this case, each order would support more than 75 days of average demand.

On the other end of the spectrum, when carrying costs are quite high (40 percent) relative to the cost of replenishment, EOQ suggests smaller inventories (as the result of smaller orders) and the order cycle is slashed to almost one-third its former value (now, just over 26 days).

Underlying assumptions

The assumption being made in the construction of the EOQ formula is that the cost of carrying inventory is linear. That, at a five percent rate, a one dollar decrease in inventory on-hand will lead to a five cent reduction in carrying costs to the firm. Similarly, at a 40 percent carrying cost rate, a one dollar decrease in inventory on-hand will lead to a 40 cent decline in carrying costs.

Unfortunately, the linear relationship assumed by the EOQ formula simply does not exist.

When calculating the cost of carrying inventory, a large number of factors are generally considered:

1. Warehouse space rental (or equivalent)
2. Utilities expense
3. Property tax expense
4. Maintenance expenses on the warehouse and warehouse equipment
5. Inventory write-offs/write-downs
6. Other inventory shrinkage
7. Financing expenses for the warehouse, the equipment, and the inventory itself
8. Insurance expenses on the warehouse and the inventory
9. Labor expenses related to warehouse operations

When inventory is reduced $1,000 in a warehouse with a calculated 25 percent carrying cost, what are the likely real impacts on expenses for carrying inventory?

1. Warehouse space rental (or equivalent) – no change
2. Utilities expense – no change
3. Property tax expense – no change
4. Maintenance expenses -  no change
5. Inventory write-offs/write-downs – possibly some change, but not necessarily at the same “average” rate
6. Other inventory shrinkage – same as above
7. Financing expenses for the warehouse, et al -  no change
   Financing expense on the value of the inventory – some change possible
8. Insurance expenses on the warehouse, et al – no change
   Insurance expenses on inventory – some change
9. Labor expenses – no change

In short, only three of the nine items involved in calculating the cost of carrying inventory would likely change based on $1,000 reduction in inventory. That’s because increases or decreases in the volume and dollar amount of inventory held in a warehouse operations produce relatively large but non-linear changes operating expenses.

As inventory grows, changes like adding a second shift in the warehouse, acquiring additional warehouse space, or adding manpower to handle increased volumes happen incrementally. The EOQ formula has no way to account for these non-linear changes to operating expenses. Therefore, your EOQ decision-making my be entirely off the mark for success and increased profits.

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What’s the answer?

To manage your inventory quantities, I would highly recommend the application of Dynamic Buffer Management. [Click on the link and read the article there.]

To deal with non-linear changes in your enterprise—decisions that may lead to major changes in inventories (increases or decreases)—you need a broader formula that considers your system (your enterprise) as a whole. That would be this one:

Where,

• ROI = Return on Investment
• delta-T = Change in Throughput 
• delta-OE = Change in Operating Expenses
• delta-I = Change in Inventory or demand for other Investment

This formula would cover changes like adding a second shift (change in Operating Expenses) or building a new warehouse (change in Investment).

Think about. Contact me if you need further clarifications.

Getting started in Business Intelligence (BI) on a budget

This is a simple demonstration as to how you and your firm can get started turning the data that you already have into the information you desperately need using tools you already own. The task of turning data into information for decision-making is the essence of business intelligence (BI).

So, here we go.

Everybody has data

Everybody has data. Many companies are wallowing in data. What they are lacking is “information.”

Read my posts here and here for more about the differences between data, information and knowledge.

Quick! Take five or ten minutes to peruse the following table of data and write down everything that you see in these data to help make decisions about the firm’s future.

I will give you one hint: the column identified as ‘ARPAC’ is “Average Revenues per Active Customer.”

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Okay. Times up.

Hold on to your list.

Turning data into information—simply, easily, cheaply

In order to produce what follows, I used only Microsoft® Excel™ and its native ability to access databases to fetch and refresh data.

Here’s the first graph I produced:

This is nothing more than a simple bar graph of column “SOSales” (Sales Order Sales, as opposed to Invoiced Sales, for example) shown in the data above. I used Microsoft’s native capabilities to add a “trend line.”

By looking at this simple graph, several questions might come to mind that would bear further investigation:

1. Why have our monthly sales dropped from just over $8 million a month to an average of about $6 million per month over these 29 months?
2. Why or how were able to produce about $11 million in sales in July of 2008? What did we do differently? How can we build on what we learned in that experience?
3. Is my drop in sales related to lost customers?

The next graph that I produced looked like this:

This graph answered my question number three above—at least partially. Month-to-month our firm has stayed pretty steady in terms of the number of active customers served. The firm is hovering right in the 250-customers-per-month range.

On the one hand, that is good. It means the firm is steady in this regard, but it does provoke other questions that would need to be answered through further digging:

1. We are serving about 250 customer per month, but is the same 250 customers, or do I have high turnover rates for customers?
2. Are we constantly having to spend precious marketing resources to capture new customers, or do we have a high volume of repeat business?

But wait! If we are not loosing customers (at least in numbers), but our sales are falling off (in aggregate), what is that telling us?

The third graph I produced was “Average Sales per Active Customer” (month-to-month). This graph clearly shows that between January 2008 and May 2010, the firm’s average sale per active customer fell from about $32,000 per customer to under $25,000 per customer.

Here again, this graph immediately provides clues worthy of further, more detailed, investigation:

1. Are these different customers buying less product? Or, are we serving pretty much the same customers, but they are just buying less from us?
2. Either way, we should figure out why: Are they buying similar quantities, but our prices (and, perhaps, margins) have shrunk over this period? Or, are they buying smaller quantities of merchandise or services from us?
3. Either way, we should find out why: If they are buying smaller quantities, is some of that business going to our competitors?

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Next steps

As you can see, turning the data into information allows our mind to quickly digest it and move toward decision-making. In some cases—perhaps many cases, when you first start—the process will lead to further information gathering.

On the other hand, you will sometimes discover that tribal knowledge already present in your organization will help you take immediate steps to begin making more money tomorrow than you are making today. Frequently, those steps involve no investment at all. Sometimes all it take is understanding better what is happening. Other times, a simple policy change permits significant increases in Throughput and profits.

After all, isn’t that really what you want to do—not spending six-figures on a new business intelligence “solution”?

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Read more here about unlocking “tribal knowledge.”

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How I did it step-by-step

1. Identify the data
2. Build a SQL Server view or query
3. Connect Microsoft Excel to the data
4. Build the graphs

Total time: about 2 to 2.5 hours

Business Intelligence for the coming year

Recently I was asked by a business writer for my recommendations for “BI New Year’s Resolutions.” I doubt my response was what the writer had hoped for, since many business blogs and publications garner support from advertisers. And, when you are doing that for a living, you really want to write things that are supportive of the kinds of products your advertisers supply. These days, since business intelligence (BI) is all the rage, there are a lot of dollars being proffered for advertising of upscale business intelligence solutions.

For better or worse, I don’t have to worry about that. (Of course, my income is smaller as a result.) But, here’s what I wrote—along with some other advice to round it out.

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BI New Year’s Resolution

RESOVED – I will never, ever, ever again undertake a BI project just because someone in my organization thinks “it might pay-off.” Instead, I will faithfully resolve to calculate—in advance—the expected ROI (return on investment) for the project.

I have learned my lesson: BI is not like an engine oil additive: departments can’t just “pour it in and expect the company to run smoother, faster, longer and get higher mileage” through some mystical power brought to them by the BI fairy.

In calculating the ROI, I will also remember that “approximately right” is fart better than “precisely wrong,” so will not waste my firm’s precious resources trying to hone a number to perfection before taking action—especially in this tough economy.

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The second question to which this writer asked me to reply regard “top BI trends” for 2012. Once again, I’m pretty sure I let her down. Here’s what I wrote:

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BI Trends for 2012

In 2012, an increasing number of small-to-mid-sized firms will discover that, to get started in BI, they do not need to make six-figure investment. In fact, they may not even need to make a five-figure investment.

If they can unlock “tribal knowledge” and begin to understand what to measure in order to make a real difference in the Throughput of their system (i.e., the whole firm), chances are they can make use of tools they already have like Microsoft® Excel™ to capture data from their ERP system directly via ODBC (open database connectivity) or OLEDB (object linking and embedding for databases). This may lead to insights, and those insights may lead them to market segmentation or other innovative profit-improvers. They do not need expensive software to build a simple, yet valuable, dashboard so they can start making more money sooner—rather than later.

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In the next post, I will provide a concrete example of how simple BI can be done using tools your firm probably already owns.

(c)2008, 2009, 2010, 2011 Richard D. Cushing

Technology Wars 2: The Search for More Profits

Almost a year ago I wrote an article entitled, “What does ‘demand-driven’ really mean?” in which I outlined a view of a supply chain driven end-to-end by real-time (or near real-time) demand feedback. My recollection of this writing was triggered today by an article that appeared today on the Financial Times website: “Technology: Smarter software helps minimise discounting.”

In the FT (Financial Times) article, Claer Barrett writes:

“As retailers grapple with falling consumer spending and rising costs, the smart use of technology is proving a valuable weapon.

“Creating a point-of-sale linked supply chain is the latest tactic that larger retailers are employing in order to manage inventories and minimise discounting.”

Among other things, Barrett discusses how the entire supply chain—from the retail all the way back to the manufacturer—is being forced to cope with greater and greater uncertainty. At the same time, Barrett correctly points out that today’s “consumer is more empowered than ever before” via online shopping and price-comparison options.

Barrett’s discussion of the matter leads directly to another topic on which I have written here a number of times—namely, market segmentation. [Click here for more.] Retailers everywhere are learning to collect and leverage high volumes of point-of-sale data, mostly through the proliferation of loyalty programs. [Note: I just checked my pockets. I must be a member a more than dozen loyalty programs ranging from pet supply stores to gas stations and more.]

Between a rock and hard place

Even with improved ability to segment the market and identify buying trends and patterns, the whole supply chain is still caught between the “opposing problems of excess inventory and stock shortages,” as Barrett puts it. Barrett, however, is far too gentle, I think. The horns of the dilemma should really be stated as

excess inventory versus stock-outs.

Almost everyone who has had responsibility for managing inventories of any kind knows exactly what I’m talking about. Being short on stock (low inventories) does not on whit of damage. But being out-of-stock means

1. Lost sales of the out-of-stock goods
2. Lost sales on other goods that may have been purchased by customers seeking the out-of-stock item(s)
3. Potentially, customers lost temporarily or even permanently to competitors

As I have stated elsewhere, the value of losses resulting from out-of-stock conditions—if calculated at all—is almost always vastly understated.

However, on the other end of the spectrum, even though the supply chain suffered out-of-stocks on (almost always) the most popular items, they are almost never able recoup the profits on those items for which they are overstocked.

No.

In fact, chances are they will have to liquidate their overstocked item at or below the price they paid for them. Hence, Barrett’s reference to finding ways to “minimise discounting.”

The key to creating more profits is a “demand-driven” supply chain

My article on a demand-driven supply chain suggests technology that is within the reach of almost every retailer today—not just the big-box merchants. But it requires management to seek two things that they are presently overlooking in far too great a degree;

1. The true cost of out-of-stocks to their operations and to the entire supply chain
   
2. The return-on-investment available to them for building a truly connected and collaborative supply chain

If you are a mid-market retailer, distributor, wholesaler or manufacturer, do not delay in pursuing the discovery of ways to create for yourself a sustainable competitive advantage even in a very challenging economy.

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Further reading: Dynamic Buffer Management (DBM)

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Richard D. Cushing is a senior solution architect at RKL eSolutions in Lancaster, PA.

Finding Common Ground Between CFO and COO–Part 10

[Continuation…]

 

Some key factors in creating Irrefusable Offers

What are some of the key elements that should be considered by the CFO and COO when creating “Mafia Offers”?

Well, if the CFO and COO have come to properly understand their market and market segmentation through analytics (simple is better), the next step is to unlock “tribal knowledge” within the organization so the customer’s experience and customer’s desired results are clearly understood for each market segment. If necessary, that may mean identifying a market segment constituted of only one customer.

Make the offer learning, anticipating or filtering

The irrefusable offer must be one that lightens the burden felt by the customer, improves the customer’s experience, and produces better results for the customer. Offers that are learning, anticipating and filtering are such offers.

Take a look at the offer give in Example 1 in Part 8 of this series. This offer lightened the burden on the customer by reducing the customer’s need to store and handle large quantities of inventory month after month. The billing method, in turn, improved the cash flow for the customer, as well.

The offer was, in fact, anticipating the customer’s needs and filtering the volume down to the quantities actually required while still providing the prices to which the customer was accustomed under the previous ordering practices.

This offer, however, could have been made even more learning, anticipating and filtering. Suppose they had offered to simply replace the quantity actually consumed each month, rather than a flat 50,000 units per month. This may have been even more appealing to the customer.

Make the offer customizable

Buyers ranging from individuals buying one-offs via the Internet to professionals buying for big-box merchants today are influenced by customizable offers. Sometimes it is the actual product that is customized (e.g., made to specification, personalized, color or style options). However, even typical commodity offers can be customized.

When the product itself cannot or is not offered as customized, that does prevent the offer itself from being customized. Offers may be customized around several parameters:

• Delivery method – online, next-day, same-day, free-freight, in-person, vendor-managed and so forth
• Delivery quantities – incremental deliveries, truck-load, on-demand quantities
• Payment terms – credit card, 90-days same as cash, consumption-based invoicing

The goal, of course, in any customization in the offer is to improve the customer’s experience and results.

Make the offer upgradable

Without renegotiating the whole deal, an upgradable offer allows the customer to add-on, extend, or improve upon an existing trading agreement. This is especially valuable where the market may be subject to significant changes—as are most markets today. I think most CFOs and COOs would agree that they would much rather keep a customer through an upgradable offer than to risk losing the customer because the customer feels that they must renegotiate “the whole deal” anyway.

Again, looking back to the offer give in Example 1 in Part 8 of this series, you can easily see that this offer was, indeed, upgradable. The offer could be extended to buy more of the same product, or additional products could be purchased under the same plan.

Make the offer online, interactive or one that provides near real-time feedback

Offers that lead to or involve sharing information in real-time or near real-time are also generally more able to be learning, anticipating and filtering. The close contact created by interaction between seller and buyer may also lead to valuable insights that could lead to more customized or upgradable offers.

Some time ago I had opportunity to discuss a new software purchase with the CFO a rapidly growing $350 million enterprise. I asked him what he thought about the software, but when he replied, he did not really talk about “the software,” at all. He said:

“The company has this great approach to support. They offer an online knowledgebase that is searchable and provides a wealth of helpful information. But what’s even better is that they monitor activity on the support site 24-hours a day. If it seems you are not finding the answer to your question after a couple of attempts, a dialog box pops-up and a live support person proactively offers to help you resolve your issue right then and there.”

Clearly, this buyer of “software” was far more impressed with online, interactive, real-time feedback from support than the software itself. This CFO has purchased “software,” but what he got was a better experience and improved results from his purchase.

Accompany the offer with anytime access and response

In a world where the typical customer is empowered by Internet access to so many options, providing an offer that includes anytime access or response is likely to improve the customer’s experience and results. This is proven by the previous example where the CFO mentioned the fact that the support site was proactively monitored “24-hours a day.”

In fact, I personally find that my clients feel much more “connected” with me when I give them my cellular phone number and assure that they are free to call me (literally) 24-hours a day if they need my assistance.

[To be continued…]

Finding Common Ground Between CFO and COO–Part 9

[Continuation]

So, what are the keys to constructing irrefusable offers (Mafia offers)?

Market segmentation

The CFO and COO must come to understand the key components that go into their trading partners’ experience and what their trading partners view as improved results. More importantly, they must begin to see that different trading partners or different market segments have different experiences and seek different improved results.

In order to get a better understanding of how to segment your market, the CFO and COO should employ a combination of market analytics (business intelligence) and tools to unlock “tribal knowledge” from within the organization itself.

As the figure above suggests, different target markets will find value in differing aspects of “the offer.” Some will find the value in a product’s ability to be customized or adapted to their specific application. Others will find greater value in how the product is delivered (speed or online). Still others will find greater value in intangibles such as VMI (vendor-managed inventory) or the ability to receive small, more frequent shipments,while achieving the same price-breaks as larger orders. It is impossible to know until the CFO and COO take time to analyze and understand how and why they sell—or fail to sell—into various markets.

Capabilities

Another factor concerning which the CFO and COO must come to agreement regards the firm’s capabilities. What can be done within the firm’s capabilities to supply an improved customer experience for various segments of the market? In addition, what can be done—still within the firm’s capabilities—to help assure that the customers in various market segments are getting better results than the competition is delivering?

Understand that, until the firm’s various market segments are understood clearly, it is impossible to even formulate the right questions around “capabilities” and how to apply them toward the creation of irrefusable offers.

Creating an operating partnership with your customers

The really great and long-lasting irrefusable offers stand above the rest because they create a durable competitive advantage for both the vendor and the customer. The offer brings your firm and your customer’s firm into an operating “partnership” that produces better—and improving—results for your customers while increasing your own firm’s Throughput and profits. This combination makes three very happy parties—the CFO, the COO and the customer(s) involved.

This may mean the such irrefusable offers may sometimes need to be tendered to the customer at a higher level than the typical “buyer.” Creating and presenting the offer may involve the CFO and COO in joint discussions with their counterparts in the customer’s organization, where the value of the irrefusable offer may be more fully understood and appreciated.

Establishing these offers and resulting agreements at higher levels knits the customer’s management team with you—the vendor’s management team—in a way that makes it increasingly difficult to dislodge the vendor from the customer’s new way of doing business. Customer loyalty becomes a strong factor at this point, and the number of “touches” between the customer and the vendor tend to increase over time.

[To be continued…]

Finding Common Ground Between CFO and COO–Part 8

[Continuation…]

Creating Irrefusable Offers: Example No. 1

A relatively small manufacturer had several large accounts in its market. However, due to the firm’s smaller size, the large accounts were quite reluctant to buy from it. Apparently, the buyers were afraid that the smaller manufacturer would not have the capacity to deliver the large quantity orders on time.

By setting about to understand its customers and its market better, this small manufacturer was able to discover that, while the larger accounts bought in large quantities—in order to get the price-breaks associated with such large quantity purchases—the firms did not actually consume the large quantities immediately. Instead, they ended up warehousing them for some period of time.

Here is the customizable/upgradeable offer that got the smaller manufacturer in the door with these big accounts:

“Agree to buy from us in the same quantities you have been buying from our competitors (e.g., 250,000 units at a time). We will match the competitors’ prices for these items during an introductory period—so you can gain assurance that we can deliver and you are fully satisfied with the quality. However, since you generally consume these at a rate of about 50,000 units a month, that is how we will deliver them to you and invoice you for them.

“In this way, we will save you the costs and headaches related to storing and handling the excess inventory. Additionally, you may customize your delivery rate—up to double—for any given month with just an email or a phone call to (XXX) XXX-XXXX and seven (7) days’ notice.

“Once you are fully satisfied with our service and quality, you may upgrade this plan by a) adding more products to the purchase agreement, and/or b) increasing your purchase volume on any product at special rates.”

This offer turned out to be a win-win. It helped the customers improve their results while allowing the small manufacturer to do business with the larger accounts without having to make additional investments in production facilities. (It was hard for the small manufacturer to produce 250,000 units at once, but they could easily produce and deliver 50,000 to 100,000 units a month without fail.)

This offer provided additional benefits for the large manufacturers: By taking delivery and being invoiced for the smaller quantities on a monthly basis, the large manufacturers actually experience improved cash-flow.

Creating Irrefusable Offers: Example No. 2

A pasta-maker wanted to take over a supermarket chain’s ordering process by employing vendor-managed inventory (VMI). When the chain’s management balked at the idea, the pasta company developed its own irrefusable offer. The pasta-maker said that they would park a truckload of pasta on the lot of the chain’s distribution center. If, at any time, the pasta-maker failed to deliver on-time what the chain needed, the chain could take whatever was short from the truck free of charge.

This irrefusable offer gave the chain’s management and buyers the assurances they needed to move ahead with the VMI plan. The pasta-maker, however, was so capable that the truck did not have to remain in the chain’s parking lot for long.

Here, again, we see the irrefusable offer being constructed around Toyota’s definition of quality—the customer’s measure of the experience and improved results. Also note that this irrefusable offer was targeted at a market of one with a consciousness of the customer’s specific needs and concerns.

[To be continued…]

Finding Common Ground Between CFO and COO–Part 7

[Continuation]

In Part 1 and Part 2 of this series, we introduced the following two diagrams as a pair:

 

This first is a generic statement of dimensions as “effectiveness” and “differentiation.” The second diagram restates these dimensions in terms familiar to anyone who has seriously touched upon constraints management or the Theory of Constraints. Here the dimensions are “Increasing Throughput” and “Breadth of Market through Irrefusable Offers.”

The concept was first introduced by Dr. Eliyahu Goldratt in his book It’s Not Luck. Later he clarified by saying, that a Mafia offer is “an offer [your trading partner] can’t refuse.”

But what, exactly, is an “irrefusable offer” (aka: “unrefusable offer” or “Mafia offer”)?

Irrefusable Offers

The concept behind the “Mafia offer” or the irrefusable offer is that it is an “offer you make to your market—your prospects and [or] customers—to make them desire your products or [and] services” [Theory of Constraints Handbook, p.604] so much that they simply cannot refuse to do business with you. And, to be effective, the offer must be one that your competition cannot or will not easily copy.

Rephrasing that statement using Toyota’s definition of quality, it means making an offer where the customer anticipates an experience and results that far excel anything else in the marketplace. Getting to this point requires the CFO and COO to understand the various market segments that they serve in fresh, new ways.

A good starting point to is to ask: “What is some part of my market or industry has a unique need—or a unique combination of needs—that is not being met by any of our competitors?” In order to gain this insight, the CFO and COO should begin to see how they can blur products into services and services into products.

Between you and your target markets sit several “customizable” options—the augmented product. For example, your market may be office supplies—rather generic. But the way you deal with that generic market can become a dramatic differentiator and lead to the creation of irrefusable offers.

• Product  - Consider the selection, quality and variety of your product offerings.
• Connection – Consider that the experience of doing business with a sales representative in person is different from doing so over the phone; a paper catalog is a different experience than buying on-line; even the quality of the on-line experience can make a difference (e.g., What does your Web store remember about your customers’ preferences in products, delivery methods, and so forth?)
• Speed – Buying a product that is delivered same-day is different that buying a product that is delivered tomorrow or next week
• Other intangibles – Taking credit cards for payment is a different experience than custom billing; Offering payment terms on major purchases is different from a one-size fits all policy on payments; Personalizing products—colors, sizes, quantities, imprinting, etc.—all change the customers’ experiences and results; ad infinitum

Beyond those augmented product options, today’s sophisticated trading partners are looking for even more, and rather than seeing these as insurmountable challenges, the CFO and COO should be joining forces to find ways to make some or all of these things happen.

• Customizable – More and more products and services are being made customizable to the customers’ specifications and desires.
• Upgradeable – Customers almost always see more value in products where the life-cycle is extended through built-in or optional upgrades. Consider, for example, smartphones and other mobile devices where the operating systems are automatically upgraded with little or no user intervention. Consider those products now being offered with guaranteed trade-in values at the end of a normal lifecycle. Consider those products that a modular, where the customer can start with the “basic” (lower cost) model and extend the product’s capabilities over time by purchasing add-on functionality.
• Online – Even greeting card companies are now offering “smart” greeting cards that are interactive with online services. This drives the customer experience into completely different realms when compared to the simple card-and-envelope. Consider the ability to now offer interactive online training to accompany a product or service purchase. The training need not be limited to only how to use the product or leverage the service. Why not consider customized training about how to best apply the product/service in a particular industry (for example) to increase profits for your customers?
• Anytime access and response – Firms are now offering online knowledgebases to help their customers get more out of the products and services their customers buy. But some have gone a step beyond. Some firms now proactively monitor their customers’ online activities on their website and, when it seems the customer may be having difficulty finding the solution to their problem, a remote agent offers interactive real-time customer support 24-hours a day, seven days a week.
• Learning, anticipating and filtering – As your customers interact with your firm, your firm needs to be constantly learning so that your firm’s response will anticipate your customers’ future needs and filter out those elements that are clearly of little or no use (at present) to your customers. It is wonderful if a hotel chain places in the guests’ rooms a complementary snack for members of its rewards program. But it is even better if, over time, the hotel chain learns that a particular guest prefers chocolate chip cookies to peanut butter cookies and Perrier to spring water, so that no matter which hotel the guest visits, his or her favorite snack is always what is provided.

[To be continued…]