A change in attitude in the public sector is vital if consultants are to make the contribution they should be making to government objectives. This applies to providing value for money for taxpayers, streamlining the public sector and generally running the country more efficiently.
Above all, the government needs to spend less time commissioning reports from consultants and more time thinking about exactly what it wants consultants to do, not only in a practical sense but also at a strategic level.
The public sector has set itself the objective of delivering services more quickly, giving better value for money and increasing its capacity to respond to change.
But whereas the public sector is striving for new efficiencies and reduced costs, when it comes to its attitude to consultants it is all too common for the government to develop a split personality.
On the one hand, the government is aware that consultants can offer in-depth expertise and value for money. But on the other hand, public sector organisations contain politically minded people who are often frustrated by the high level of consultants’ earnings.
Whenever the debate focuses on spending on consultants, you can be pretty sure that most of the emphasis will be on the sums of money involved, with very little on the benefits derived from the expenditure.
If the discussion does focus on cost issues, it is usually because of the way many public sector organisations use consultants and the type of individuals they hire.
Unfortunately, government is too willing to use consultants as convenient manpower substitutes.
Such a strategy stems from laziness; after all, hiring a manpower substitution consultancy can be a lot easier than focusing on the problem that needs to be addressed.
The public sector really needs something it does not actually receive
very often genuine skills transfer deriving from relatively short-term projects.
Skills should be embedded in the minds of the consultants and in the processes of the public sector organisation.
Some smaller consultancies are good at skills transfer, and so are some larger consultancies. But it is more a question of attitude.
The issues a public sector body really needs to address when it is contemplating hiring a consultant are:
- Consultancies must be genuinely focused on giving the benefit of transferred knowledge to the public sector organisation.
- If they are not willing, they should consider whether they are really suitable for working with government bodies.
- Consultancies should also be willing to get in, do the job and get out again. In other words, they should be prepared to get away from a model of engagement that very often relies on milking a client for every penny.
Ultimately, consultants should aim to help make the public sector bodies for which they are working more agile.
Then they will have staked a real claim to be deserving of the privilege of consulting to government.
This article appeared in Computing on 7th of August 2008.
Please read more about our work in Government
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.
