Image: Island Peak, Nepal, by McKay Savage, CC license

“Scope,” or “footprint” in software terms refers to the number of business processes that an application will “cover,” or enable.  The scope of an accounting system is usually: general ledger, accounts payable, accounts receivable, fixed assets, P&L and balance sheet.

The scope has to fit the application, and vice versa, and it has to be feasible for the project team and deliver the benefits expected to pay back the investment in the new system.

Too big a scope can overwhelm the team and the application you select.  It will also cost more.  Too small a scope might not be worth the time and expense, and may not yield the financial benefits expected.  A creeping scope starts out small and feasible, then as the project progresses scope is added in the form of requests for features and functions not originally planned.

Money pits are usually found at the end of projects with too big of a scope or a creeping scope.

How do you find the right scope?

Determine which areas of the business would benefit the most from a new or better application. Can you define the specific problems that are leading your enterprise to consider new software? Where are those problems located – in what functional areas and related to which current (legacy) system? Is the problem that a) a particular application is too limiting; b) a group of applications are islands and that integration of them would yield benefits; c) none of your applications are integrated; or d) something else?

Consider a range of scope options to find the optimal one. In some cases, expanding the scope of a new application beyond “problem areas” can be the optimal choice. The process is iterative, and you should consider several alternatives. For example, implementing a new accounting system may satisfy most of a company’s needs and produce a good ROI on its own. But expanding the application footprint to, say, payroll and purchasing, may result in an even better return because it simplifies integration costs, eliminates more manual work, and may strategically be a better decision.

Set up a framework to evaluate each scope alternative. In a framework (Excel comparison) you can evaluate each scope option according to such factors as cost, complexity, length of time to implement, risk to the business, ROI, required internal resources and strategic value. Then you have a logical basis for your decision.

The scope of an ERP project does not have to be huge. You can be selective in what processes to migrate to an ERP system, and you don’t have to convert everything at once – both of these steps will reduce the overall risk of the project. For example, you can implement demand planning systems first to shake out the bugs in what is traditionally a complex and parameter-sensitive application. The core financial systems of an ERP can also be phased in first before everything else.

Image by Nicolas Will, CC license

Behind every idea is a set of assumptions.  These assumptions can be exposed by simply by asking “why”?

When it comes to good technology management, it’s your job to test these assumptions, to kill the losing propositions or to make them more viable as sound investments.  Sometimes these assumptions are wrong – and a lot of them need to be right in order for a project to succeed.

Many people don’t realize the number of assumptions they make when a technology project is launched. Among them:

• what they saw in the demo or pilot will work in the real world;
• the software will meet all the business requirements that were specified before the project started;
• the team won’t have to make any customizations other than what was already identified;
• users will quickly learn and accept the new system;
• the project will be completed on the promised date.

In my book I described a hypothetical conversation between a manager and a CIO/CEO.  The manager was explaining that “the new system will give us real-time visibility of our vendor inventories and plant inventories, and instead of waiting for reports we’ll see our inventory positions and planned production and receipts real-time.”

Taken at face value, this statement implies acceptance of the following assumptions:

1. The way we think of “real-time visibility” of inventories, production and receipts is the same as what the system can provide.
2. The view of said data will be in a useful format and will provide all the data we need to make better/faster decisions.
3. These better/faster decisions will enable us to let our customers order within a shorter lead- time window and will reduce our on-hand inventories.
4. The savings from lower inventories and the additional sales from our late-order customers will more than pay for the cost of this new system.
5. A change in business process (i.e., how we manage inventories and production) would not produce these same benefits.
6. Out of all of the possible system solutions this one is the best choice from an IT strategy, cost and ongoing support standpoint.

A pause for a minute to question these six assumptions may well be the most valuable minute ever spent on the proposed project.  All kinds of havoc and wasted money can be avoided just by testing these assumptions.

And as you can see you don’t have to be an IT expert to successfully manage technology.  You just have to use common sense, by testing the logic that if we do X, then we will receive Y benefits.  If you are going to invest in technology, you may as well do it the right way.

The short answer to why corporate software costs so much is that implementing it takes so long, even if everything goes perfectly, which happens exactly as often as Haley’s Comet passing through our skies. It’s expensive for one reason: specialized, and therefore expensive, skills. It takes expensive skills to:

• write the software in the first place;
• modify it to your precise business needs; and
• install and test it and fix problems before you can use it.

The three biggest cost buckets of a software investment are implementation, software modifications, and the cost of delays or disruption to the business.

What is “implementation”? It is the process of making your business function using the new software, or “integrating” the software into your business, however you choose to look at it. Companies have different philosophies about this; some insist the software must be modified to accommodate the way the business functions; others believe in keeping the software as “vanilla” as possible by changing processes to fit the way the software was designed to work.

There is probably a happy medium.  I think the more you modify a program the more trouble you can expect.  It is not unusual to spend a (low) percentage of the project cost on modifications.

“Implementation” is also the process of matching each step in your business process to corresponding steps in the software. A business “process” is usually something like “ship a customer order” or “receive a shipment from a supplier.”

There might be 100 or so distinct business processes in a company, each with five to eight steps or transactions involved, so a software implementation could involve matching all of those 500 to 800 steps or transactions to the new software, and that takes time, knowledge of your business, and knowledge of the new software.

That’s why implementations are expensive: high cost per hour multiplied by many hours.

But if a perfect project is expensive, imagine how expensive a delayed or failed project can be. Failure is the norm, according to some studies, defined as over budget, not meeting implementation dates, or not delivering functionality as expected.

I would add to that list, from personal experience, failure also includes unexpected business disruption, like temporarily shutting down a manufacturing plant or shipping to your customers a day late. So the fact that software implementations are perceived to be wildly expensive is not just because software implementations are wildly expensive anyway – they also have a high failure rate, which only adds to the cost.

Image: a toy replica of the DeLorean Time Machine from the 1985 film “Back to the Future,” photo by J.D. Hancock, CC license

Company P is a firm I have worked with that helps companies to achieve ambitious goals. One of the firm’s methods is to engage in a “Merlin” exercise – so named for the legendary magician who claimed to come from the future. In this exercise, groups describe in words or illustrations the future of their company in three, five or more years, pretending that ambitious goals have already been achieved.

How did the company get there? What do processes look like? The more detail, the better. How did we get rid of all that non-value-added work? How did we double business with the same number of people?

This is the approach you need in order to define how your software investment is going to change your business results.

Ignore the systems for now. For now, don’t try to imagine your current system with great new features. That is too limiting. For this part of the project, keep “the system” generic. It can and should appear in your future plans, with specific capabilities, but not as a specific system. When you have selected specific software and become aware of its capabilities and limitations, come back and re-draw the future processes as they will be executed with that particular application.

Define what problems are fixed in the future state. The present must have some characteristics that people want to change, or else there would be no interest in a new system investment. So start with a few problem statements to articulate why you want the future to be different from the present, such as “While visiting customers, the sales team cannot access order history nor place additional sales orders, resulting in lost revenue to the company.”

Imagine. When the problems identified are resolved, what does that look like? What would it look like if, for example, the problem of having to delete and re-enter a customer order just to change it were fixed? “Service reps can retrieve from the system a customer order, go into an edit process, make any change required, including products ordered, quantities, delivery dates, method of payment, and shipping options, then save the order.”

Don’t be constrained by today’s business situation, type of system architecture, or preferences of senior management. Don’t limit your thinking to just small problems. Imagine a bigger picture, years into the future, when the company is transformed from what it is today…what would that look like?

Start with the big picture – “Sales have doubled” – and work backwards to specifics from there. “We started selling through a web portal.” The big picture is the eventual outcome you want, the specifics – a web portal, for example – will be the things around which new business processes will be formed. The new processes are what you want the new technology to enable.

Software-as-a-Service is challenging the paradigm that software is a thing you buy, take back to your office and install. Looking back some day, we might shake our heads and wonder why any enterprise ever thought it had to purchase and physically install a copy of millions of lines of code that ran on a computer within its premises, just to transact day to day business.

On-premise going the way of cassette tapes……?

The market is receptive to more and more SaaS solutions, and software firms are positioning themselves to offer those products. Most of the big, traditionally on-premise software providers now offer at least some of their applications in SaaS form. For you, this will mean more choices.

But remember this: SaaS applications do not guarantee perfect performance and 100% uptime. They are still computer programs running on a server somewhere, and if those programs are buggy, unstable, corrupted, or lack proper expert support you will land in the money pit just as sure as if you bought that same buggy and unstable application and installed it in your own data center.

Are there any good reasons why you would want a traditional on-premise application?

Yes: security is one reason, in certain circumstances. No matter how demonstrably secure a third party may seem, you simply may not want to entrust your data security to a third party, period.

Your customers, particularly, may want the relative or perceived assurance of your own firewall surrounding your applications and their data. Their business relationship is with you, not the company hosting your applications.

You may already have economies of scale suited to on-premise hosting – plenty of server capacity, a built-in support staff, and developers on your team who are capable of building out the application the way you want it.

If you are positioning the application to be used by several divisions within your company, you may also want central on-premise hosting. You may want to tightly control modifications to the “core” system and also manage access permission levels among users, as well as the total number of users. These actions can significantly reduce per-user costs.

With SaaS applications, you still need to do the same due diligence you would do with a traditional on-premise application. The fit analysis, testing, and project management are largely the same, as are the same precautions to avoid the money pit. You can still spend a fortune modifying a SaaS application, as well as integrating it to your other systems and pulling data out of it for analysis purposes.

Photo: astronaut Eugene Cernan salutes American flag on the surface of the moon, December 1972, Goddard Space Flight Center, CC license.

Our team felt pretty good one day in early March, 2012, when we went live on an SAP system — manufacturing, inventory, order processing, MRP, demand planning, purchasing, shipping and receiving, and finance – with no business disruption, in 90 business days, and 30% under budget

We arrived at this happy conclusion because of (good) decisions made early in the project — decisions about strategy, scope, preparation, technology selected, and the makeup of the team.

How do you drive success — especially if you’re not savvy to enterprise software in the first place?

1. Can you, in a three minute speech to your CEO, sell the project: why you need $2 million and 15 people for nine months, and how your company strategy and your customers demand this kind of investment? If not, start over.
2. Only pursue projects with an unambiguous and demonstrably positive ROI based on realistic assumptions. Leave the great ideas, dreams and wish lists behind.
3. Leave no room for surprise costs. You’ll find them in these categories: additional user, site, or department licenses, support fees, custom programming, server, network, PC and operating system upgrades, future version upgrades, project consultants, and backup staff and travel for the team.
4. Use only your best people for the team. Nothing is more powerful than an experienced, focused, and motivated team with a mandate from top management and a simple, clear objective. If you can’t afford to free up your best people, you can’t afford the project.
5. Decide what is included in the project and what is not, clearly and as simply as possible. Ruthlessly prevent any changes to the scope.
6. The software you choose: prove that it works in other enterprises, preferably companies like yours. It should be familiar to consultants or programmers you may need, now and in the future.
7. Pick technology your company’s users can easily master. You can do lots of damage with people who don’t understand the new systems they have to use.
8. Insist on a full under-the-hood evaluation of the fit of the system with the business. Have the software vendor prove that it meets your requirements by piloting your business scenarios in the application.
9. Protect as much of the business as possible from the inevitable problems of a new system. Break up the “go-live” into manageable parts and have a manual backup plan to keep the business running.
10. Remember this quote from software legend Frederick P. Brooks: “How does a software project come in six months late? One day at a time.”

Image by Nick Ayres, CC license

Big software project failures can frequently be tied back to decisions made at the very beginning of the project.

As the government struggles to launch healthcare.gov after the expenditure of several hundred million dollars, it’s logical to question the original decision to build from scratch software programs that may in part have already existed.

In 2001, Nike made the decision to big-bang its launch of new supply chain planning software with thousands of suppliers and distributors all at once, resulting in a massive disruption to its business and $100 million in lost sales.

An overly complex design and an urge to impress the public were two big reasons – made very early in the project — for the colossal breakdown of Denver Airport’s $560 million baggage handling system.

In each of these cases, the main reasons for failure could have been nipped in the bud at the very beginning.

How to avoid failure from dumb decisions at the start? To illustrate, I’ll describe what not to do. I’ve seen every one of these decisions made at some point in some project I’ve worked on over the years.

Launch the project for the wrong reasons. Believe that new software will fix a broken or inefficient process.
Fool yourself about the ROI. Show the CFO numbers you know are a fantasy, just to get approval for your new system.
Make the scope bigger than necessary. Launch a big ERP project when all you really need is a sales planning and trade promotion system, or an updated financials and payroll application.
Develop the software yourself, even though there are reasonably good packaged applications available on the market.
Assign the project to people who are already swamped and who live in different time zones. Run most of the project via conference calls to save money on travel.
Put your weakest people on the project team. Select a project manager who is leading a project for the first time, or who logically should run it based on the organization chart. Don’t free up the critical subject matter experts that will be needed; they’ll find the time somehow. Just empower the team and everything will run fine.
Ensure the application is fully modified to match every nuance of your business so people are comfortable with it. Don’t worry if the solution becomes too complex – it’s software so everything can be programmed.
Don’t place a fixed deadline or budget for project completion; plans need to be flexible to account for unforeseen difficulties, or opportunities for expansion of the solution to satisfy more of your company’s needs.
Ensure everything is launched all at the same time. Why drag out the project in phases?
Don’t try to manage the project with a structured methodology. Doing so will unduly restrict the free flow of ideas and creativity that are essential. Most project methodologies are a waste of time and only serve to increase the workload on the project team.

You’ve seen it before – how projects gain institutional momentum even though the hard reasons for it aren’t clear.

An expensive multi-year project is hatched from the need for some level of management somewhere, to “move the enterprise forward” by technology-enabling new and improved processes.

Ideas – the seeds of projects — have a way of gaining momentum without the right level of rigorous questioning and unbiased analysis. Notice how a project, slim as the specifics might be, gets an impressive name, such as Phoenix, Gemini or Athena, and then almost automatically has credence as a legitimate, important initiative that must be done. Once the project gains notoriety in this way, there is a bias to produce something from it, and often that bias to do something ends up being the purchase of a new system or systems.

Years ago I worked for a company that announced a project to “transform” the company chiefly by “integrating” different departments; we’ll call this project Excalibur. A team was formed, made up of the best and brightest, from a cross-section of functional departments. A lot of full-day meetings were held.

I wasn’t involved in Excalibur, yet, so I didn’t know what the meetings were about. But I do know that the first thing — no, make that the only thing — the Excalibur team set out to do was to evaluate packaged software solutions…for what, it wasn’t immediately clear. But it occurred to me that the team was completely bypassing important steps, like stating a problem and business goals, identifying broken processes or dysfunctional parts of the organization, and defining a desired future state.

Epilogue: the project took nearly five years to complete, and resulted in replacement of four legacy applications with a new, interconnected ERP system. Two years after the completion of Excalibur, a new project was launched to replace everything with another ERP system.  I don’t know how much was spent on Excalibur, but we had a lot of consultants around for four or five years, and they weren’t free.

Yes, there must be a peculiar psychology to the decisions leading to projects that cost a lot of money but don’t produce results.  Maybe it’s just a reflection of human nature: wanting to be part of something big, visible, and important.  That’s risky though, if you look at the percentage likelihood of pure success of large IT projects based on studies to date, and if you plan on telling the truth when it comes to evaluating success at the end.

Recognizing that your enterprise might be in this situation – drinking the Kool-Aid, as it were – is a good first step toward avoiding the ensuing money pit.

Studies over the past 15 years show enterprise software project failure rates ranging between one-third and two-thirds. Failure is defined in various ways – over budget, taking much longer than planned to implement, causing major business disruptions, or simply abandoned. 

The OASIG Study

OASIG, an organizational management group in the UK, commissioned a study in 1995 that involved interviews with 45 experts in management and business who had extensive experience with information technology projects either as consultants or researchers. The in-depth interviews revealed a dismal 20%-30% success rates for IT projects, and the reasons cited for the overall poor track record were:

• Failing to recognize the human and organizational aspects of IT;
• Weak project management; and
• Unclear identification of user requirements. 

The Chaos Report

The Standish Group is a research and advisory firm that in 1995 published The Chaos Report, which found

• Only about 15% of IT projects were completed on time and on budget;
• Thirty-one percent of all projects were canceled before completion;
• Projects completed by the largest American companies had only about 42% of the originally proposed features and functions.

The firm extrapolated the results to estimate that in 1995, eighty thousand projects were canceled, representing approximately $81 billion in wasted spending. 

The KPMG Canada Survey

In 1997 accounting firm KPMG studied why IT projects fail. The top reasons were:

• Weak project management, including insufficient attention to risk management;
• Questionable business case for the project;
• Inadequate support and buy-in from top management. 

The Conference Board Survey

In 2001 The Conference Board surveyed 117 companies that had started or completed ERP software projects. The results showed that:

• Forty percent of the initiatives did not produce the expected benefits within a year of completion;
• On average respondents reported spending 25% more than expected on the implementation and 20% more on annual support costs;
• Only one-third of the respondents said they were satisfied with their results. 

The Robbins-Gioia Survey

In 2001, management consulting firm Robbins-Gioia queried 232 companies across a range of industries about their IT investments, particularly investments in ERP systems. Of the companies that already had an ERP system in place or were in the process of implementing one:

• Fifty-one percent said the implementation of the new system was unsuccessful; and
• Forty-six percent said they believed their organization didn’t know how to use the ERP system to improve business results.

My take on these studies is this: Projects fail for many different reasons, but nearly all of those reasons can be tied back to human factors. The likelihood of success is directly correlated to the decisions you make, the strength of your project team, the way they manage the project, the way you manage the team, and particularly the strength of your project manager (PM).

Software is like no other product on earth – it is a collection of millions of lines of instructions telling a computer what to do. You can’t “see” software; reading the lines of code would tell you nothing unless you had written the code yourself, and even programmers themselves can easily forget what they did. You must imagine software, and are left to rely on what the software’s creators say about it.

That good software is indispensable goes back to one of the first-ever software projects: an effort in the early 1950s to link together data from radars along the Eastern seaboard that were monitoring possible air and seaborne threats to the United States. Software, it was discovered, could collect, compare and plot radar data on paper much faster than human beings could.

But from software’s early beginnings as an industry in the 1950s and 1960s, business managers have struggled to understand the systems they buy, and the people and firms that market them.

In his excellent history of the software industry, Martin Campbell-Kelly describes the origins of software programming in the 1950s: “Only weeks after the first prototype laboratory computers sprang to life, it became clear that programs had a life of their own – they would take weeks or months to shake down, and they would forever need improvement and modification in response to the demands of a changing environment.” Some things haven’t changed.

Mr. Campbell also describes what must be one of the earliest maddening software experiences. General Electric had purchased a Univac computer in 1954, but it took “nearly 2 years to get a set of basic accounting applications working satisfactorily, one entire programming group having been fired in the process. As a result, the whole area of automated business computing, and Univac especially, had become very questionable in the eyes of many businessmen.”

We are 60 years into the commercial software industry, and while applications have become much more powerful, they are still prone to failure.  Large projects still fail at a high level, and the sums spent are much greater than 60 years ago.

So the challenge remains: not to build more powerful or smarter applications, but to build and integrate software into an enterprise in a predictable, reliable and cost-sensible way.