Selling Brittle Applications
October 7, 2009
Has it ever occurred to you that software salespeople get a bad rap? In the popular imagination, they have blood dripping from their fangs. But in my experience, that’s not what they’re like at all. don’t. The ones I know are pretty decent folk, live in the suburbs, maybe even coach soccer. Not one of them would actually throw their mothers under a bus in order to get the deal. At least, I don’t think they would.
So what accounts for this reputation? Well, in the course of writing this series of blogs on brittle apps, I think I’ve come up with an answer of sorts.
Start with a fact that you should know, but maybe haven’t paid much attention to. Good software salespeople don’t sell software. They sell benefits. They don’t try to confuse you with features or functions or architecture; they try to make you understand what those things will do for you.
This is what they should be doing. After all, the buyers of software don’t really know about or understand what the features do, and they don’t have the patience to figure out exactly how the features produce the benefits. You’re a CEO or CFO, you want to get to the point. What is the value that these products deliver?
Software salespeople have developed this reputation, I think, because people have discovered or heard or found that the benefits aren’t available. And they think the salesperson knew this all along and, like some snake-oil salesman was promising a cure for cancer in order to wrest the last dollar out of some old lady’s handbag.
But in my experience, that’s not what’s going on at all. The salespeople actually have a fairly rational, if optimistic view of their product. They know that the products are designed to achieve certain benefits; they can see themselves how the design could work; and they probably know of customers who have achieved the benefits they should achieve. At worst, they’re like a Ferrari or a Jaguar salesman, who focuses on the riding experience and doesn’t feel it is incumbent upon him to bring up the repair records.
People like Dennis Moore would go even further in the software salesman’s defense, and perhaps they’re right. They would say that the salesperson is more like a good physical trainer, who can genuinely promise to get you in better shape if you’ll work out. If after you buy, you don’t want to put in what it takes to get the benefits, that’s your problem not theirs.
So is Dennis right (assuming he would agree with the words I’m putting in his mouth); when somebody buys software and underutilizes or puts it on the shelf, is it entirely their problem. Well, no. I think it would be if they realized how brittle these applications really are. But in my experience, they rarely do. They buy this Ferrari, go out on a Sunday afternoon, and only when they find themselves riding back next to the tow truck driver, do they find out what they’ve bought.
So whose problem is it? Well, I’ve already gone on too long. You’ll have to wait until the next post.
Why Develop Brittle (High-Risk) Apps?
September 25, 2009
“Brittle” design isn’t limited to enterprise application software. You can find brittle design in cars, bridges, buildings, TVs, or even the vegetable bin. (What are those 1/2-pint boxes of $5.00 raspberries, 3/4 of which are moldy, but examples of brittle design?)
What do brittle designs have in common? The designer chose to accentuate high performance at the expense of other reasonable design parameters, like cost, reliability, usability, etc. A Ferrari goes very, very fast, and it feels good when it goes fast, and that’s a design choice. And it’s part of the design choice that the car requires a technician or two to keep it going fast for longer than an afternoon.
So why are most enterprise applications brittle? You can see this coming a mile away. It was a design choice. The enterprise applications in question were designed to be the Ferraris of their particular class of application. They were designed to do the most, have the most functionality, be the most strategic, appeal to the most advanced early adopters, be the most highly differentiated, etc.
To get Ferrari-like performance, they had to make the same design choices Ferrari did. They had to assume the application was perfectly tuned every time the key was turned, and they had to assume that the technicians were there to perform the tuning.
Enterprise applications, you see, were intended to run on the best, the highest-end machines (for their class). They were intended to be set up by experts. They were intended to be maintained by people who had the resources to do what was necessary. They were intended to satisfy the demands of good early-adopter customers who put a lot of pressure on them, with complex pricing schemes or intricate accounting, even if later on, it made setting the thing up complex, increased the chance that there were bugs, and made later upgrades expensive.
This wasn’t bad design; it was good design, especially from the marketing point of view. The applications that put the most pressure on every other design parameter got the highest ratings, attracted the earliest early adopters, recruited the most capable (and highest-cost) implementers, etc., etc. So they won in the marketplace and beat out other applications in their class that made different design choices.
I lived through this when I worked at QAD. At QAD, the founder (Pam Lopker) made different design choices. She built a simple app, one that was pretty easy to understand and pretty easy to set up and did the basics. And for about two years, shortly after I got there, she had the leading application in the marketplace. And then SAP and JDE and PeopleSoft came in and cleaned our clock with applications that promised to do more.
Now, none of the people who actually bought SAP instead of QAD back then or chose (later) to try to replace QAD with SAP did this because they really wanted high performance, per se. They wanted “value” and “flexibility” and “return on investment” and “marketable skills.” They literally didn’t realize that the value and flexibility came at a cost, that the cost was that the application was brittle and that therefore, the value or flexibility or whatever was only achievable if you did everything right.
If they had realized this, would they have made different choices?
I don’t know. I remember a company that made kilns in Pittsburgh that had been using QAD for many years. The company had been taken over by a European company that used SAP, and the CIO had been sent over from Germany to replace the QAD system with the one that was (admittedly) more powerful. He called me in (years after I had worked at QAD) to help him justify the project.
I looked at it pretty carefully, and I shook my head. Admittedly, the QAD product didn’t do what he wanted. But I didn’t like the fit with SAP. I was worried that the product designed for German kiln production just wasn’t going to work. I didn’t want to be right, and I was disappointed to find out that two years later, despite very disciplined and careful efforts, he was back in Germany and QAD was still running the company.
I’m glossing over a lot, of course. There are secondary effects. Very often, the first user of an application dominates its development, so the app will be tuned to the users strengths and weaknesses. It will turn out to be brittle for other users because they don’t have the same strengths. Stuff that was easy for the first user then turns out to be hard for others.
Two final points need to be made. First, when a brittle application works, it’s GREAT. It can make a huge difference to the user. Brian Sommer frequently points out that the first users of an application adopt it for the strategic benefit, but later users don’t. He thinks it’s because the benefit gets commoditized. But I think it’s at least partially because the first users are often the best equipped to get the strategic benefit, whereas later users are not. I think you see something of the same issue, too, in many of Vinnie Mirchandani’s comments about the value that vendors deliver (or don’t deliver).
Second, as to the cause of failure. Michael Krigsman often correctly says that projects are a three-legged stool and that the vendors are often blamed for errors that could just as easily be blamed on the customers. Dennis Moore often voices similar thoughts. With brittle systems, of course, they’re quite right; the failure point can come anywhere. But when they say this, I think they may be overlooking how much the underlying design has contributed.
It may be the technician’s fault that he dropped the beaker of nitrogycerin. But whose brilliant idea was it to move nitroglycerin around in a beaker?
A Flaw in Business Cases
September 19, 2009
A software business case compares the total cost of software with the benefits to be gained from implementing the software. If the IRR of the investment is adequate, relative to the company’s policies on capital investment, and if the simple-minded powers that be have a good gut feel about the case itself, it is approved.
Clearly, a business case isn’t perfect. Implementing software is an uncertain business. The costs are complex and hard to fix precisely. Implementation projects do have a way of going over; maintenance costs can vary widely; the benefits are not necessarily always realizable.
That’s where the gut feel comes in. If an executive thinks the benefits might not be there, the implementation team might have a steeper learning curve than estimated, the user acceptance might be problematic, he or she will blow the project off, even if the IRR sounds good.
Business cases of this kind are intended to reduce the risk of a software purchase, but I think they’ve actually been responsible for a lot of failures, because they fail to characterize the risk in an appropriate way.
There’s an assumption that is built into business cases, which turns out to be wrong. The fact that this assumption is wrong means that there’s a flaw in the business case. If you ignore this flaw (which everybody does), you take on a lot of risk. A lot.
The flaw is this. Business cases assume that benefits are roughly linear. So, the assumption runs, if you do a little better than expected on the implementation and maintenance, you’ll get a little more benefit, and if you do a little worse, you’ll get a little less.
Unfortunately, that’s just not the case. Benefits from software systems aren’t linear. They are step functions. So if you do a little worse on an implementation, you won’t get somewhat less benefit; you’ll get a lot less benefit or even zero benefit.
The reason for this is that large software systems tend to be “brittle” systems. (See the recent post on “Brittle Applications.”) With brittle systems, there are a lot of prerequisites that must be met, and if you don’t meet them, the systems work very, very poorly, yielding benefit at a rate far, far below what was expected of them.
This problem is probably easier to understand if we look at how business cases work in an analogous situation. Imagine, for instance, the business case for an apartment building. The expected IRR is based on the rents available at a reasonable occupancy rate. There is, of course, uncertainty, revolving around occupancy rates, rentals, maintenance costs, quality of management, etc. But all of this uncertainty is roughly linear. If occupancy goes up, return goes up, maintenance goes up, return goes down, etc. The business case deals with those kinds of risks very effectively, by identifying them and insuring that adequate cushions are built in.
But what if there were other risks, which the business case ignored? These risks would be associated with things that were absolutely required if the building was to get any return at all. Would a traditional business case work?
Imagine, for instance, that virtually every component of the building that you were going to construct–the foundation, the wiring, the roof, the elevators, the permits, the ventilation, etc.,–was highly engineered and relatively unreliable, required highly skilled people who were not readily available to install, fit so precisely with every other part of the system that anything out of tolerance caused the component to shut down, etc., etc. The building would be a brittle system. (There are buildings like this, and they have in fact proven to be enormously challenging.)
In such a case, it is not only misguided to use a traditional business case, it is very risky. If one of these risky systems doesn’t work–if there’s no roof or no electricity or no elevator or no permit–you don’t just generate somewhat less revenue. You generate none. Cushions and gut feel and figuring that an overrun or two might happen simply lead you to a totally false sense of security. With this kind of risk, it’s entirely possible that no matter how much you spend, you won’t get any benefit.
Now, businessmen are resourceful, and it is possible to develop a business case that correctly assesses the operational risk (the risk that the whole thing won’t work AT ALL). I’ve just never seen one in enterprise applications. (Comments welcome at this point.)
The business cases and business case methodologies that I’ve seen tend to derive from the software vendors themselves or from the large consulting companies. Neither of these are going to want to bring the risk of failure to the front and center. But even those that were developed by the companies themselves (I’ve seen a couple from GE) run into a similar problem: executives don’t want to acknowledge that there might be failure, either.
But the fact that the risk makes people uncomfortable doesn’t mean that it’s a risk that should be ignored. That’s like ignoring the risk that a piton will come out when you’re mountain climbing.
Is the risk real? Next post.
Brittle Applications
August 31, 2009
In a previous post, I said that MRP was a “brittle” application, and a commenter questioned me. What is a “brittle” application? Is this a technical term? What makes MRP brittle? All good questions.
A brittle application is one that doesn’t work at all unless a lot of disparate conditions are met. MRP, for instance, doesn’t work unless all the data is right, people know how to use the program, the demand for the products is stable, purchasing is also committed to minimizing inventory levels, etc., etc.
The notion applies to a lot of other programs besides MRP, though I’ve rarely heard the term used. But notice that it brittleness isn’t so much a feature of the program as it is the purpose to which the program is put.
Let’s take a simple example: a word processing program. For normal purposes, a word processing program in this day and age is not brittle. A rank novice can use it to type and print. But even today, if you want to use, say Microsoft Word, to put out a 16-page brochure, complete with illustrations, well, good luck, is all I can say. You try to get an illustration and have it float and change the size and put in a table, and–well, just try it, it’s a nightmare. So, to put a 16-page brochure together, Microsoft Word is brittle, but to print out a letter, it’s not.
The point about the MRP program that QAD wrote, which follows the APICS standard religiously, is that it’s brittle relative to the purposes for which it was intended. Pam and Karl and Evan (the founders of QAD) really believed that QAD’s could do supply chain management for manufacturing facilities very effectively. My point was that the program is too brittle. To get things right, you have to get all the data right and keep it right, etc., etc. And if you don’t, what you have is an overwrought and overcomplicated Kanban system, without Kanban’s virtues.
Are there other enterprise application systems that are brittle? Lots and lots of them, I think. Almost all the old, Siebel-style CRM systems were simply too brittle; they depended too much on the good-will of the salespeople, the accuracy of the sales model embedded in the system, the reliability of the sales cycle, etc., etc. You wouldn’t think that financial systems are brittle–after all, they have to work–but they often had components that were overly brittle: cash management systems, for instance, and fixed asset systems and budgeting systems.
What do most companies do when they have an overly brittle system? They use the system for lesser purposes. And they feel REALLY bad about it. So, the Microsoft Word user makes a brochure that is far less fancy, but more manageable, and the QAD MRP user uses the product for tracking inventory. And both of them keep on saying, “Well, one of these days, I’ll get around to really making this product sing.”
They shouldn’t. Brittle applications are brittle for a reason. A lot of the time, it’s because they’re really a special-purpose product, but yours is not that purpose. Some of the time, they’re brittle because they’re badly designed. Some of the time, the model they’re using (MRP is a good example) just doesn’t fit the situation you’re in. In any of the cases, the fact is that they really can sing for the right user, but that doesn’t mean it’s your fault if they don’t sing for you.
What do you do if you have a brittle app that isn’t singing? Give up on it. It won’t work for you. Get another app, one that works. Or change the process. Or just accept the fact that it will never work the way you thought it would.
In any case, good luck.
Is Supply Chain Knowledge Key for ERP Implementations?
August 22, 2009
I used to work at QAD, a small manufacturing software vendor. I subscribe to a QAD chat group, and occasionally people ask questions like the one in the title.
It sounds as if the person asking is peddling something–who knows–but it’s an interesting question nonetheless. What kinds of knowledge are necessary (key) for an ERP implementation? If you run a manufacturing company, is APICS (that is, supply chain) knowledge particularly important?
Certainly, QAD used to think so. When I was an employee, you got a bonus for becoming APICS certified. (APICS is the American Production and Inventory Control Society; to get certified, you had to learn how MRP worked and how inventory should be managed.) And certainly, when the product was designed, the focus was on matching supply and demand. The product was built originally for Karl Lopker’s sandal manufacturing business, and the idea was always to have simple, usable product that managed inventory well.
So you would think that the answer, at least for QAD users, is, “Of course APICS knowledge is key. Duh.” But I don’t think so.
You see, while I was at QAD and then for some years afterward, I looked at a fair number of installations. And what I saw was disheartening, at least if you believed in good supply chain practices. The systems weren’t really using good supply chain practices, at least as APICS defined them.
Let me give you an example, which APICS-trained people will understand immediately. One of the ideas of these systems is to reduce the amount of inventory you have on hand at any one time. To do this inside the system, there are two parameters that you have to set, lead time (which is the amount of time it takes for an order to be fulfilled) and safety stock (the amount you want to have on hand at all times). The longer the lead time or the higher the amount of the safety stock, the greater your inventory expense.
So what would you say if discovered that in not one or even two installations, but many, the safety stock and lead time numbers for most of the inventory were set once, en masse, and then never set again? Well, I’ll tell you what to think. These figures, which are key to making the system work, are not being used.
Now this was not just true of QAD Software; it was equally true wherever I went, no matter what software was installed.
So doesn’t this say that supply chain knowledge is key, after all? If they had supply chain knowledge, wouldn’t they have paid more attention? At first, I thought so. But then after a while, I realized that more supply chain knowledge would have made very little difference.
You see, that’s not why they were using the software. All these companies, it turns out, didn’t really care about getting supply chain stuff right. They managed the supply chain fairly sloppily–tolerated a lot of inaccuracy and suboptimal behavior–and they got along (in their minds) just fine doing that. They didn’t want to put in the kind of care and rigor that is the sine qua non for doing with these systems what they were designed to do.
What were they using the software for? Well, mostly to manage the paperwork virtually. Please don’t cringe, Pam, if you happen to be reading this. This is not a hack on you. The plain fact is that the companies needed to keep track of their commitments (orders), their inventory, and their money, and that’s what they used the system for. They needed a piece of paper that told people what inventory to move that day and where to move it to. And the system gave it to them.
To do this, though, you didn’t need much APICS knowledge or, if you didn’t believe in APICS’s recipes for inventory management, other supply chain knowledge. All you really needed was to be able to count, which most of the users could do without being APICS-certified.
So is supply chain knowledge key for an ERP implementation? Not at all. You can have perfectly happy users who have got exactly the nice simple implementation they need without much supply chain knowledge at all.
This answer, of course, raises lots of questions. What is key? Why do these companies tolerate sloppy supply chain practices? Wouldn’t they be better off if they cleaned up their act. Herewith, brief answers.
What is key? At a rudimentary level, the financials. You have to get the basics right, here, or you’ll never close your books. In a system studied recently by a grad student at Harvard Business School, 65% of the inventory records were inaccurate. Can you imagine the upset if 65% of your account balances were incorrect?
Why do they tolerate sloppy supply chain practices? I think it’s largely because more finely tuned systems are much more brittle. They take a large amount of care and feeding and their ability to take hard, rude, unexpected shocks is limited.
And wouldn’t they do much better using the systems? In many cases, no. You see, at most of the companies I’ve run into, the MRP/APICS model that QAD (and every other software vendor) provided is not actually all that accurate. To make a really significant difference, you need more sophisticated tools that are better suited to the specifics of your supply chain.
Comments welcome.
Delivering Sourcing Optimization
August 6, 2009
It’s a plain fact that there are certain kinds of math problems that even bright people don’t solve very well and computers solve better than we do. Some of these look surprisingly simple. If you’re a retailer, when should you mark down product and by how much? Or if you’ve got to make six deliveries, should you use one truck and make six stops, two trucks with three each, etc.
Entrepeneurs in the world of enterprise software have recognized this fact for a long, long time and have seen an opportunity there. They develop so-called optimization software, which solves an essentially mathematical problem and then provide it in various forms to the market. A few have provided only the engine itself, most of them ending up in I-Log, and many more that provide optimization solutions that address specific problems, like supply chain optimization, markdown optimization, or the subject of this post, sourcing optimization.
Now if there’s one thing that’s completely clear about optimization software, it is that the track record has been disappointing. I’m not just talking about the overpromising and underdelivering that afflicted the big-name supply chain optimization vendors. (No names, but you know who you are.) I’m talking about really wonderful products, like Joe Shamir’s ToolsGroup, which have struggled to put their tools in the hands of people who need it.
Sourcing is no exception to the general rule. In sourcing, optimization came to the fore when companies like FreeMarkets or Digital Freight wanted to set up sourcing “events,” where possibly hundreds of bidders could bid on thousands of line items, offering discounts for bundles of selected lines. What if A bids X for lines 1, 2, and 3, and B bids Y for lines 2, 3, and 4, etc.? This is one of those math problems that linear programming solutions solve better than human beings do.
A number of vendors still in the market place (you know who you are) proceeded to develop solutions for setting up and managing these events, which of course did a lot more than just figuring out which bids to accept. And to some extent, they worked; they did change the way many companies do business, and sourcing events are now fairly normal, with several large companies being big proponents.
But in my (admittedly somewhat limited) view, the optimization piece has been relatively unimportant. Certainly some companies have developed some good optimization algorithms, and they are used, but in the events I’ve seen or heard about, it’s not clear to me that the solutions they offered were actually all that optimal, and the reaction of buyers that I know to the solutions they offered have been tepid, shall we say.
I’m not surprised, as I say, because I’ve seen similar reactions from users of other optimization software.
Now I have a degree in math, and I’ve taken a course in linear programming. I know that the solutions they give you are better than what people can come up with by themselves. So are the people who don’t like these solutions just grousing? That’s certainly what most vendors think.
Well, the other day, I got a glimmer of the answer from some terrific research done by Vishal Gaur of Cornell University. (See my earlier post, “An Automated Replenishment System.”) He found in his case study that a solution produced by optimization software had a highly suboptimal operational effect because it was optimizing around the wrong things. The math was done perfectly, but the problem had been set up incorrectly.
This is always a problem in principle when you set optimization software chugging away. The software draws a box around the problem and finds the point inside the box with the best available solution. If you draw a different box (usually a larger one), the solution will be different, and will take longer to find.
In Professor Gaur’s case, the software developer had drawn the wrong box around the problem. Now what’s interesting here is that the software developer never knew that he’d done anything wrong. He delivered the software, and the IT people who were using it expressed satisfaction. And you might think, “Well, so what, even if it drew slightly the wrong box, it got roughly the right answer.” But in fact, when you change the box, you change the answer completely. So in this case, the users had to replace (manually) all the solutions the software offered (manually) with better and completely different solutions.
If you have optimization software, in other words, you have to draw the right box, or the answers that it gives you are not better than what you can provide, they are worse, often much, much worse.
Now look at how this applies to sourcing optimization. Let’s say that you set up the problem in one way. (You only allow bids from certain vendors, for instance, and you require that they offer discounts of a certain percentage.) If you draw the box differently, you will come up with quite different answers.
I was discussing this problem with Garry Mansell, president of TradeExtensions, a small sourcing optimization vendor. He argues that the only way of solving this problem is to provide a lot of services, along with the software. The experts that he provides (it just so happens, of course, that he’s in the business of providing this pairing) can keep the sourcing on track and make sure the right box is drawn.
Now I react to most honeyed words from vendors the way I react to offers of honey for my tea. (Hint: “No, thank you.”) But this struck me as roughly right. The problems that I’ve seen with implementations of myriad kinds of optimization software wouldn’t be solved, then, by fixing the software. It would be solved by helping people to make sure that they’re drawing the right box around the problem.
So who knows. Maybe Mansell is right. (Or maybe he’s just selling software. Or both.) But it seems to me to be a useful thing to keep in mind. If you’re looking at sourcing optimization software (or, more generally, any optimization software), don’t buy it and don’t use it, unless you have some serious experts, who can help you make sure that you drew the right box.
The Applicator 