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It's generally true that the more advanced a technology becomes, the less you notice it. Fly in a First World War biplane and you won’t forget for one moment you’re flying in a plane: the noise, the goggles, the wind in your face and the precarious progress will leave you in no doubt at all. But fly across the Atlantic in a modern-day jet and it’s easy to forget you’re in a plane at all; especially if you fly at night, when big planes resemble flying cinemas, even down to the dimming of the lights.
Similarly, when Charles Babbage’s partial prototype cogwheel computer performed calculations, the grinding of its cogwheels left no-one in doubt they were seeing a machine in action, and a pretty cumbersome one at that.
But today, computers are so much part of our lives that we often aren’t even aware of them.
Close fit
When you use technology for business, the closer the fit the system is to your needs, the better. Ideally, you won’t, as far as possible, want to notice the technology – and this certainly applies when you’re using enterprise resource planning software. The key question is: what kind of ERP systems are likely to be the best fit to your requirements, giving you maximum utility and letting you get on with your business activities without being especially conscious of the technology? ERP is the part of business that deals with the supply chain, which is the basis of all modern commercial life. Yet mention to most people who aren’t involved in the supply chain that you work in it, and their eyes may start to glaze over.
ERP may not at first sight seem inherently interesting – but unless it works smoothly, things everyone wants to happen, won’t. Today, as business grows ever more complex, the supply chain – and indeed the whole area of enterprise resource planning – is more elaborate than it’s ever been. People’s demands as consumers and customers are not only becoming more extensive in terms of sheer quality, they are also growing more and more precise.
Another crucial factor is that the pressure on inventories has never been as great as it is now. Customers are usually entirely – indeed blissfully – ignorant of just how massive inventories must be if they are to end up with exactly what they want, when they want it. ERP systems play a crucial role in supporting an organisation’s logistics activities. But in this role, they are going through a revolution that in many respects challenges the notion of what an ERP system is and what it should be doing.
Beyond tradition
It is increasingly recognised by ERP practitioners that there are many downsides to what might be referred to as ‘traditional’ ERP systems. These systems have evolved from the ‘best of breed’ model that was popular through the 1980s into very comprehensive and functionally rich products that fully support the internal processes of most businesses, from quotation to fulfilment and beyond.
But traditional ERP systems have a number of significant disadvantages, the biggest of which is that they impose a rigid structural process on anyone who wants to use them. This wouldn’t be a problem if real-life processes – and especially the often highly complex processes of ERP activity – themselves followed a rigid structure. But they don’t. To take one example…say you’re using a traditional ERP system to carry out a sale, and you have a query for the customer and need to send them an email (to explain, for instance, that the colour they asked for is not available and to ask them to specify another colour).
To do this, you will in fact have to exit the traditional ERP system and create and send the email as a separate action.
The problem is, businesses and their customers work in an unstructured way. And that’s the whole point. Traditional ERP systems want you – the users – to work in a structured way, because they’re designed to work like that too. But business can’t ever be truly structured. Ultimately, no matter how big the organisation might be, customer transactions involve dealing with individuals whose needs are unlikely to be predictable, straightforward or indeed necessarily always rational.
For example, a recent survey of business users and their working practices found that a full 85% of the activities involved in what is on the face of it an ERP transaction, are typically outside the kind of activity that traditional ERP systems carry out. What the survey found, in essence, is that about 85% of business activity is unstructured. This finding amounts to a challenging statistic for the ERP industry.
Certainly, it vindicates ERP professionals who have found that traditional ERP systems are limited in their effectiveness for supporting business activity. The implication of the study is that traditional ERP systems shoehorn organisations into a rigid way of doing things that does not suit the real world at all.
Trio of problems
In practice, this tendency of traditional ERP systems to constrain users into operating in a way that is unrealistic and inefficient is only one of three key problems that these systems bring users.
The second major issue is that traditional ERP systems are difficult to use. To quote the CIO of one large company, recently describing his traditional ERP solution: “The problem is that while the ERP system has become more pervasive and important, a large percentage of our employees would rather eat worms than log onto the system for even the simplest task.” Hardly an indication that the system has become a barely visible and seamless part of their daily work!
The third problem is that, partly because traditional ERP systems are difficult to use, they inevitably come bundled up with a requirement for mass and in-depth training of users.
In response, newer ERP platforms are being developed that allow the unstructured elements that form part of practical ERP activity to be seamlessly included in the user interface and in the transactional processes. These systems are based around the principle of service oriented architecture (SOA).
An SOA-based system can be designed and configured to ensure that at its hub is the user’s need to gain access to all the services required to complete the action. In practice, if companies are looking to install a new ERP system or to replace an existing one, it makes abundant sense for them to be fully aware of state-of-the-art innovation in this essential area of business software. The eventual aim is to eradicate, over time, the difference between structured and unstructured processes.
In fact, the whole notion that some elements of an ERP transaction are ‘unstructured’ really arises because traditional ERP systems restrict the kind of actions that are possible using them – and so oblige users to think of some actions as unstructured. This thinking comes about because of the inadequacies of the technology – just like someone refusing to fly as a passenger in a Boeing 747 because they haven’t been issued with goggles!
Among the non-traditional vendors, Microsoft is taking the SOA idea one step further by basing its ERP technology on what is known as role-based systems – in other words, systems that integrate all the role requirements needed by the user during the transaction process. The appeal of the role-based approach is that there is no practical limit on what can be included and presented to users on a single screen: if the resource can be computerised, it can be incorporated into the transaction process.
In summary, new-look ERP systems that welcome the unstructured elements of transactions are bringing an exciting democratisation to the ERP world. These new systems are easy to use, and give you desktop and click-of-a-mouse access to all the functions you need to complete a business transaction quickly and efficiently. Also, because these new systems are easy to use, the cost of training is greatly reduced. This results in a significant improvement on the return on investment against traditional ERP solutions and a lower overall cost of ownership. For ERP systems, the future is already here.
This article appeared in Conspectus in October 2009.
Please read more about our work in Microsoft Dynamics at our Dynamics portal.
1. INTRODUCTION
Application Integration is the biggest cost driver of corporate IT. While it has been popular to
emphasise the business process integration aspects of EAI, it remains true that data integration is a
huge part of the problem, responsible for much of the cost of EAI. You cannot begin to do process
integration without some data integration.
Data integration is an N-squared problem. If you have N different systems or sources of data to
integrate, you may need to build as many as N(N -1) different data exchange interfaces between them –
near enough to N2. For large companies, where N may run into the hundreds, and N2 may be more
than 100,000, this looks an impossible problem.
In practice, the figures are not quite that huge. In our experience, a typical system may interface to
between 5 and 30 other systems – so the total number of interfaces is between 5N and 30N. Even this
makes a prohibitive number of data interfaces to build and maintain. Many IT managers quietly admit
that they just cannot maintain the necessary number of data interfaces, because the cost would be
prohibitive. Then business users are forced to live with un-integrated, inconsistent data and fragmented
processes, at great cost to the business.
The bad news is that N just got bigger. New commercial imperatives, the rise of e-commerce, XML
and web services require companies of all sizes to integrate data and processes with their business
partners’ data and processes. If you make an unsolved problem bigger, it generally remains unsolved.
Users and software vendors have devoted huge efforts to tackling the N2 data integration problem.
The solutions available today can be grouped into four main levels of increasing sophistication and
power:
1. Hand coding of data interfaces
2. Source-to-target mapping and translation tools
3. Integration hubs and brokers
4. Full model-based integration
This article discusses the costs and benefits you can expect at each level.
1. INTRODUCTION
Application Integration is the biggest cost driver of corporate IT. While it has been popular to
emphasise the business process integration aspects of EAI, it remains true that data integration is a
huge part of the problem, responsible for much of the cost of EAI. You cannot begin to do process
integration without some data integration.
Data integration is an N-squared problem. If you have N different systems or sources of data to
integrate, you may need to build as many as N(N -1) different data exchange interfaces between them –
near enough to N2. For large companies, where N may run into the hundreds, and N2 may be more
than 100,000, this looks an impossible problem.
In practice, the figures are not quite that huge. In our experience, a typical system may interface to
between 5 and 30 other systems – so the total number of interfaces is between 5N and 30N. Even this
makes a prohibitive number of data interfaces to build and maintain. Many IT managers quietly admit
that they just cannot maintain the necessary number of data interfaces, because the cost would be
prohibitive. Then business users are forced to live with un-integrated, inconsistent data and fragmented
processes, at great cost to the business.
The bad news is that N just got bigger. New commercial imperatives, the rise of e-commerce, XML
and web services require companies of all sizes to integrate data and processes with their business
partners’ data and processes. If you make an unsolved problem bigger, it generally remains unsolved.
Users and software vendors have devoted huge efforts to tackling the N2 data integration problem.
The solutions available today can be grouped into four main levels of increasing sophistication and
power:
1. Hand coding of data interfaces
2. Source-to-target mapping and translation tools
3. Integration hubs and brokers
4. Full model-based integration
This article discusses the costs and benefits you can expect at each level.
1. INTRODUCTION
Application Integration is the biggest cost driver of corporate IT. While it has been popular to
emphasise the business process integration aspects of EAI, it remains true that data integration is a
huge part of the problem, responsible for much of the cost of EAI. You cannot begin to do process
integration without some data integration.
Data integration is an N-squared problem. If you have N different systems or sources of data to
integrate, you may need to build as many as N(N -1) different data exchange interfaces between them –
near enough to N2. For large companies, where N may run into the hundreds, and N2 may be more
than 100,000, this looks an impossible problem.
In practice, the figures are not quite that huge. In our experience, a typical system may interface to
between 5 and 30 other systems – so the total number of interfaces is between 5N and 30N. Even this
makes a prohibitive number of data interfaces to build and maintain. Many IT managers quietly admit
that they just cannot maintain the necessary number of data interfaces, because the cost would be
prohibitive. Then business users are forced to live with un-integrated, inconsistent data and fragmented
processes, at great cost to the business.
The bad news is that N just got bigger. New commercial imperatives, the rise of e-commerce, XML
and web services require companies of all sizes to integrate data and processes with their business
partners’ data and processes. If you make an unsolved problem bigger, it generally remains unsolved.
Users and software vendors have devoted huge efforts to tackling the N2 data integration problem.
The solutions available today can be grouped into four main levels of increasing sophistication and
power:
1. Hand coding of data interfaces
2. Source-to-target mapping and translation tools
3. Integration hubs and brokers
4. Full model-based integration
This article discusses the costs and benefits you can expect at each level
1. INTRODUCTION
Application Integration is the biggest cost driver of corporate IT. While it has been popular to
emphasise the business process integration aspects of EAI, it remains true that data integration is a
huge part of the problem, responsible for much of the cost of EAI. You cannot begin to do process
integration without some data integration.
Data integration is an N-squared problem. If you have N different systems or sources of data to
integrate, you may need to build as many as N(N -1) different data exchange interfaces between them –
near enough to N2. For large companies, where N may run into the hundreds, and N2 may be more
than 100,000, this looks an impossible problem.
In practice, the figures are not quite that huge. In our experience, a typical system may interface to
between 5 and 30 other systems – so the total number of interfaces is between 5N and 30N. Even this
makes a prohibitive number of data interfaces to build and maintain. Many IT managers quietly admit
that they just cannot maintain the necessary number of data interfaces, because the cost would be
prohibitive. Then business users are forced to live with un-integrated, inconsistent data and fragmented
processes, at great cost to the business.
The bad news is that N just got bigger. New commercial imperatives, the rise of e-commerce, XML
and web services require companies of all sizes to integrate data and processes with their business
partners’ data and processes. If you make an unsolved problem bigger, it generally remains unsolved.
Users and software vendors have devoted huge efforts to tackling the N2 data integration problem.
The solutions available today can be grouped into four main levels of increasing sophistication and
power:
1. Hand coding of data interfaces
2. Source-to-target mapping and translation tools
3. Integration hubs and brokers
4. Full model-based integration
This article discusses the costs and benefits you can expect at each level.