Understanding the data mountain means getting smarter
By Stephen Leonard, IBM’s chief executive in the UK and Ireland
Published: May 10 2010 17:28 | Last updated: May 10 2010 17:28
Modern information is unlike any that has gone before – it is voluminous, extremely fast and widely varied in format.
It comes structured and unstructured; from within a company and without; it arrives on a daily, hourly and real-time basis.
At the same time, powerful tools using advanced mathematics combined with vast computing power can start to integrate financial data with information about customers, supply chain, and workforce capabilities.
And in a world of intelligent objects, greater granularity is making information even harder to fathom. Containers and pallets are tagged for traceability – as well as medicine bottles, poultry and fruit, adding more detail to the information ecosystem.
This makes using information a daunting task. But it means the business of making decisions is shifting from intuitive and experiential to fact-based, which should lead to better decision-making.
To make progress, however, each enterprise needs to look at how prepared it is to help integrate, standardise and analyse the information flooding in – a real potential problem.
Working harder and longer is not the answer. The key is working smarter, and that means having the right information and insight to drive smarter business outcomes.
Working smarter means front line business leaders know where to find the new revenue opportunities and which product or service offerings are most likely to address each market requirement.
It means business analysts can quickly access the right data points to evaluate key performance and revenue indicators in building successful corporate growth strategies. And, it means corporate risk and compliance units can recognise regulatory, reputational and operational risks before they become a problem.
Until now, acquiring, configuring and fine-tuning a system to analyse information to solve problems and uncover breakthrough insights has required technical skills out of reach for many companies.
Now, many organisations are embracing analytics technology to gain business advantage and better serve their clients. Our research shows that one in three business leaders frequently makes critical decisions without the information they need; 53 per cent don’t have access to information across the organisation needed to do their jobs.
There are, of course, challenges in undertaking analytics-driven transformations. First, and most critical, is data quality.
While 100 per cent accurate data is impossible in enterprises, it should be remembered that analytics is a journey, with successive iterations of the analytical cycle providing the gradual improvements required.
Enterprises too often assume analytics is a highly technical or a quantitative subject that should be left entirely to technology teams.
In fact, successful analytical transformations are driven by the core business leadership. The chief executive or chief operating officer should be driving analytics initiatives across the enterprise. They should ensure that every tool, technology or statistical technique becomes part of achieving the larger business goal.
A further challenge comes from trying to meet every business challenge using analytics. It is important to ensure the business does not lose confidence in the initiative by keeping the rewards incremental and demonstrating the impact of analytics at every stage. Once the basic framework is in place, value can be delivered incrementally and periodically.
For the intelligent enterprise, the future means knowing, not guessing. It means taking information and turning it into insight that can enable business leaders to make real decisions, rather than simply hope for the best.
Analytics has applications that range from helping financial markets to perform better and recognise fraudulent behaviour, to helping doctors make better diagnosis and treatment decisions.
It can also help police in crime reduction, by aggregating street level information across myriad sources. Wherever there are huge amounts of data, analytics can determine the best course of action.
Forward thinkers have, for some time, been drawing on the potential of the technology that is proliferating in the physical world and being embedded in all kinds of systems, interconnected and infused with intelligence.
In the coming decade, these ”smart” pioneers will have at their disposal new analytics technology that will become an increasingly vital source of intelligence, influence planning and take informed decision-making to new levels of sophistication.
Leaders are also beginning to acknowledge that smarter systems sometimes require change in economic and social mindsets. For example, societies may need to shift long-held views on citizen privacy, as systems generate (and share) far more personal data than before.
Societies need to ask themselves whether the benefits of smarter systems outweigh perceived civil infringements, changes in lifestyle or even up-front investment. Welcome to the “decade of smart”.
Copyright The Financial Times Limited 2010. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
Showing posts with label Business Intelligence. Show all posts
Showing posts with label Business Intelligence. Show all posts
Monday, May 10, 2010
Wednesday, December 09, 2009
Digital Business
Digital Digest – Managing Intelligence
In this multi-media Digital Business digest we examine how organisations can gather information, analyse it, and serve it up in a meaningful, usable form
Video: business intelligence in action plus panel discussions
Podcast: disparate sources – how to use data from a decentralised business in several languages The days of the Next Big Thing could be over
Maybe there will be no one idea or invention, but a wave of disruptive technologies
Does IT work? Monitoring staff requires care
Tracking workers via mobile devices raises privacy concerns
Enterprise 2.0 is vital for business
Real benefits await successful adopters of new online tools
View latest print issue and full archive
Published on December 10 2009, or download as a pdf
Related content and features
In this multi-media Digital Business digest we examine how organisations can gather information, analyse it, and serve it up in a meaningful, usable form
Video: business intelligence in action plus panel discussions
Podcast: disparate sources – how to use data from a decentralised business in several languages The days of the Next Big Thing could be over
Maybe there will be no one idea or invention, but a wave of disruptive technologies
Does IT work? Monitoring staff requires care
Tracking workers via mobile devices raises privacy concerns
Enterprise 2.0 is vital for business
Real benefits await successful adopters of new online tools
View latest print issue and full archive
Published on December 10 2009, or download as a pdf
Related content and features
Thursday, November 26, 2009
The final frontier of business advantage
The final frontier of business advantage
By Alan Cane
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
Business intelligence, information intelligence, business analytics: whatever you call it, all the evidence is that ways of turning a company’s raw data into information that can be used to improve performance and achieve competitive advantage is the topic du jour in many business leaders’ minds.
A survey carried out this year by the US-based consultancy Forrester Research revealed that of more than 1,000 IT decision makers canvassed in North America and Europe, more than two thirds were considering, piloting, implementing or expanding business intelligence (BI) systems.
“Even in these tough economic times, virtually nobody in our surveys says they are retrenching or reducing their business intelligence initiatives,” says Boris Evelson, a principal analyst for Forrester with more than 30 years experience of BI implementation behind him.
What is BI management? It is not about the technical nitty gritty of data warehousing or cleansing technology. While technologies are important – and most are good and effective, according to Mr Evelson – BI management is about ways of systematically making the most of customer information– what it is and what you can do with it.
More prosaically, it is everything that has to be done to raw data before they can be manipulated to facilitate better decision making.
Dashboard that can give a warning light on overspending
Law firm Clifford Chance has found itself learning about habits it never knew it had since analysing its spending trends through an online service provided by Rosslyn Analytics, a boutique software company based in London, writes Dan Ilett.
“It’s very flexible,” says Julien Cranwell, Clifford Chance’s procurement manager. “You can look at your data to reduce spending. We’ve identified opportunities that we wouldn’t have otherwise seen. It’s made us feel a lot more confident of the data we’ve been using.”
The company, which has 29 offices in 20 countries, used a web-based tool called rapidintel.com. The service works like a dashboard with charts and graphs to give an overview of where money has been spent.
“It aggregates and shares information,” says Charles Clark, chief executive of Rosslyn Analytics. “We extract the data in a few hours and categorise them so they go into certain buckets. We then add other data such as credit card or risk information.
“It’s presented as a ready-to-use report. The data cube never changes but they can see it from so many different angles. It’s one view of all company-wide finance, procurement, accounts payable and spend data.”
“Some of the larger areas of spending have been travel, catering and entertainment,” says Mr Cranwell. “It shows where we have varying levels of spending between offices. We are then in a position of power because we know much more about our spending patterns.
“We’ve also looked at a cost recovery programme. Using Rosslyn’s expertise we’re using a module that works on contract management.”
The firm claims to have seen a return on investment of 100 per cent within two months. “The payback period was very fast indeed,” says Mr Cranwell.
It is also about understanding the business and its processes well enough to know what questions should be asked of the data to improve performance.
The basic idea was pioneered more than a decade ago by the US computer manufacturer Teradata, which combined supercomputer performance with sophisticated software to scan and detect trends and patterns in huge volumes of data.
But it was expensive and ahead of its time. Today, high-performance, low-cost computer systems and cheap memory mean that enterprises can and are collecting and storing data in unprecedented amounts.
However, they are struggling to make sense of what they have.
In Mr Evelson’s words: “We have to find the data, we have to extract it, we have to integrate it, we have to map apples to oranges, we have to clean it up, we have to aggregate it, we have to model it and we have to store it in something like a data warehouse.
“We have to understand what kind of metrics we want to track – times, customers, regions and then, and only then, can we start reporting.”
Everybody agrees there is nothing simple about these operations. “It is a very complex endeavour,” says Mr Evelson, “and that is why this market is very immature.”
The business opportunity for BI software has not been lost on IT companies and there has already been significant consolidation in the market, with IBM acquiring, among others, Cognos; SAP buying Business Objects; and Oracle purchasing Hyperion to add BI strings to their respective bows.
Microsoft offers BI software called SharePoint Server and there is considerable interest in open source BI software from younger companies such as Pentaho and Jaspersoft.
IBM alone reckons to have spent $12bn and trained 4,000 consultants over the past few years to develop the tools and knowledge which will encourage intelligence management in its customers.
Ambuj Goyal, who leads the company’s information management initiative, argues that it is a new approach that will “turn the world a little bit upside down”.
“Business efficiency over the past 20 years was all about automating a process – enterprise resource planning [ERP] for example. It generated huge efficiencies for businesses but is no longer a [competitive] differentiator.
“In the past two or three years we have started to look at information as a strategic capital asset for the organisation. This will generate 20, 30 or 40 per cent improvements in the way we run businesses as opposed to the 3 or 5 per cent improvements we achieved before.”
But revolutions are rarely pain-free. According to the Forrester survey: “For many large enterprises, BI remains and will continue to be the ‘last frontier’ of competitive differentiation.
“Unfortunately, as the demand for pervasive and comprehensive BI applications continues to increase, the complexity, cost and effort of large-enterprise BI implementations increases as well.
“As a result, the great examples of successful implementations among Forrester’s clients are outnumbered by the volume of underperforming BI environments.”
In fact, more than two thirds of users questioned said they found BI applications hard or very hard to learn, navigate and use.
The business case for BI management is not helped by the difficulty of making a strong case for return on investment.
It is, for example, hard to decide which tools and processes should be included in the assessment – Microsoft’s SharePoint is much more than a BI tool, for example, but separating out which strands are contributing to improved revenues and which are not is a challenge.
As Mr Evelson notes: “The grey boundary lines around which process and tools to include, the multiple BI components that typically need to be customised and integrated, and the frequent unpredictability of BI system integration efforts all make BI business cases an effort not for the faint of heart.”
How, then, should executives think about business intelligence management? Royce Bell, information management specialist with the consultancy Accenture takes a robustly pragmatic view: “Business is made up of processes. Some of them may interact with the outside world, but there is a definite chain of events.
“All that business intelligence is supposed to inform, is any decision along that chain of events. The question an executive should be asking is: ‘At this point in the chain, what information do I need?’.
“Going through each and every one of your processes to be able to ask that question is hard. People are disappointed because they haven’t been able to get wisdom simply by piling all the data in one place.
“That [data warehousing and mining] sounds more exciting and more fun than going through your processes to determine what you need.”
Mr Bell believes that many executives are suspicious of the quality of the information provided by BI software: they think the data are “rubbish”, and there is no doubt that transforming data into intelligence requires clean data.
Roger Llewellyn is chief executive of the UK software group Kognitio, which has responsibility for analysing, among other things, telephone calls made by customers of British Telecom and store purchases that use the Nectar loyalty card of supermarket chain, J Sainsbury.
He says that up to 80 per cent of the price of a new contract can be the cost of cleaning the data – converting, in one case, 15 data types to a single standard.
The Sainsbury contract involves the analysis of the 20bn items purchased in the chain’s stores every nine months – enough, if typed on paper, to make an in-tray pile almost 17kms high.
How can this huge volume of bits and bytes be turned into useful information?
Mr Llewellyn gives the example of skin creams sold to counter stretch marks. Generally bought predominantly by women, if particular stores show high sales volumes, there are likely to be a lot of pregnancies in those areas – an alert for the store manager to stock up on maternity magazines, baby food and clothing.
And if most of the clothing bought is blue, there will be a lot of baby boys in the region: “From buying a jar of stretch cream, I’ve almost got you for life,” Mr Llewellyn beams.
James McGeever, chief financial officer of the US company NetSuite, which markets BI management software, underlines the importance of clean, unambiguous data in breaking down “silos” – data stored in different places and formats within an organisation: “I believe that if the same piece of data exists in two places then one will be wrong.”
The NetSuite answer for its customers is to convert all the data to one consistent type and store it in one repository: “The physical process of loading the data is not as tough as it may sound. It’s actually deciding what data to store there and how to organise your workflows that is the difficult part.”
NetSuite provides executives with tailored “dashboards”, a visual representation of the information important to their jobs.
A well-designed dashboard providing the right amount of pertinent information is a crucial part of BI according to Peter Lumley and Stephen Black of PA Consulting.
They point out that it is often forgotten that managers have limited time to absorb and act on information which, in any case, may be imperfect – if it was perfect, decision making would be no chore at all. A well-designed dashboard can help managers make the best possible decision from incomplete information.
The information, of course, has to be trusted and that is where technology can play an important part – in the automatic roll-up of data to a central repository: “Every time you go through a stage with manual intervention you have the opportunity for time delay and misinterpretation,” Mr Lumley argues.
And these mis-steps are precisely what business intelligence management hopes to avoid.
Copyright The Financial Times Limited 2009. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
By Alan Cane
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
Business intelligence, information intelligence, business analytics: whatever you call it, all the evidence is that ways of turning a company’s raw data into information that can be used to improve performance and achieve competitive advantage is the topic du jour in many business leaders’ minds.
A survey carried out this year by the US-based consultancy Forrester Research revealed that of more than 1,000 IT decision makers canvassed in North America and Europe, more than two thirds were considering, piloting, implementing or expanding business intelligence (BI) systems.
“Even in these tough economic times, virtually nobody in our surveys says they are retrenching or reducing their business intelligence initiatives,” says Boris Evelson, a principal analyst for Forrester with more than 30 years experience of BI implementation behind him.
What is BI management? It is not about the technical nitty gritty of data warehousing or cleansing technology. While technologies are important – and most are good and effective, according to Mr Evelson – BI management is about ways of systematically making the most of customer information– what it is and what you can do with it.
More prosaically, it is everything that has to be done to raw data before they can be manipulated to facilitate better decision making.
Dashboard that can give a warning light on overspending
Law firm Clifford Chance has found itself learning about habits it never knew it had since analysing its spending trends through an online service provided by Rosslyn Analytics, a boutique software company based in London, writes Dan Ilett.
“It’s very flexible,” says Julien Cranwell, Clifford Chance’s procurement manager. “You can look at your data to reduce spending. We’ve identified opportunities that we wouldn’t have otherwise seen. It’s made us feel a lot more confident of the data we’ve been using.”
The company, which has 29 offices in 20 countries, used a web-based tool called rapidintel.com. The service works like a dashboard with charts and graphs to give an overview of where money has been spent.
“It aggregates and shares information,” says Charles Clark, chief executive of Rosslyn Analytics. “We extract the data in a few hours and categorise them so they go into certain buckets. We then add other data such as credit card or risk information.
“It’s presented as a ready-to-use report. The data cube never changes but they can see it from so many different angles. It’s one view of all company-wide finance, procurement, accounts payable and spend data.”
“Some of the larger areas of spending have been travel, catering and entertainment,” says Mr Cranwell. “It shows where we have varying levels of spending between offices. We are then in a position of power because we know much more about our spending patterns.
“We’ve also looked at a cost recovery programme. Using Rosslyn’s expertise we’re using a module that works on contract management.”
The firm claims to have seen a return on investment of 100 per cent within two months. “The payback period was very fast indeed,” says Mr Cranwell.
It is also about understanding the business and its processes well enough to know what questions should be asked of the data to improve performance.
The basic idea was pioneered more than a decade ago by the US computer manufacturer Teradata, which combined supercomputer performance with sophisticated software to scan and detect trends and patterns in huge volumes of data.
But it was expensive and ahead of its time. Today, high-performance, low-cost computer systems and cheap memory mean that enterprises can and are collecting and storing data in unprecedented amounts.
However, they are struggling to make sense of what they have.
In Mr Evelson’s words: “We have to find the data, we have to extract it, we have to integrate it, we have to map apples to oranges, we have to clean it up, we have to aggregate it, we have to model it and we have to store it in something like a data warehouse.
“We have to understand what kind of metrics we want to track – times, customers, regions and then, and only then, can we start reporting.”
Everybody agrees there is nothing simple about these operations. “It is a very complex endeavour,” says Mr Evelson, “and that is why this market is very immature.”
The business opportunity for BI software has not been lost on IT companies and there has already been significant consolidation in the market, with IBM acquiring, among others, Cognos; SAP buying Business Objects; and Oracle purchasing Hyperion to add BI strings to their respective bows.
Microsoft offers BI software called SharePoint Server and there is considerable interest in open source BI software from younger companies such as Pentaho and Jaspersoft.
IBM alone reckons to have spent $12bn and trained 4,000 consultants over the past few years to develop the tools and knowledge which will encourage intelligence management in its customers.
Ambuj Goyal, who leads the company’s information management initiative, argues that it is a new approach that will “turn the world a little bit upside down”.
“Business efficiency over the past 20 years was all about automating a process – enterprise resource planning [ERP] for example. It generated huge efficiencies for businesses but is no longer a [competitive] differentiator.
“In the past two or three years we have started to look at information as a strategic capital asset for the organisation. This will generate 20, 30 or 40 per cent improvements in the way we run businesses as opposed to the 3 or 5 per cent improvements we achieved before.”
But revolutions are rarely pain-free. According to the Forrester survey: “For many large enterprises, BI remains and will continue to be the ‘last frontier’ of competitive differentiation.
“Unfortunately, as the demand for pervasive and comprehensive BI applications continues to increase, the complexity, cost and effort of large-enterprise BI implementations increases as well.
“As a result, the great examples of successful implementations among Forrester’s clients are outnumbered by the volume of underperforming BI environments.”
In fact, more than two thirds of users questioned said they found BI applications hard or very hard to learn, navigate and use.
The business case for BI management is not helped by the difficulty of making a strong case for return on investment.
It is, for example, hard to decide which tools and processes should be included in the assessment – Microsoft’s SharePoint is much more than a BI tool, for example, but separating out which strands are contributing to improved revenues and which are not is a challenge.
As Mr Evelson notes: “The grey boundary lines around which process and tools to include, the multiple BI components that typically need to be customised and integrated, and the frequent unpredictability of BI system integration efforts all make BI business cases an effort not for the faint of heart.”
How, then, should executives think about business intelligence management? Royce Bell, information management specialist with the consultancy Accenture takes a robustly pragmatic view: “Business is made up of processes. Some of them may interact with the outside world, but there is a definite chain of events.
“All that business intelligence is supposed to inform, is any decision along that chain of events. The question an executive should be asking is: ‘At this point in the chain, what information do I need?’.
“Going through each and every one of your processes to be able to ask that question is hard. People are disappointed because they haven’t been able to get wisdom simply by piling all the data in one place.
“That [data warehousing and mining] sounds more exciting and more fun than going through your processes to determine what you need.”
Mr Bell believes that many executives are suspicious of the quality of the information provided by BI software: they think the data are “rubbish”, and there is no doubt that transforming data into intelligence requires clean data.
Roger Llewellyn is chief executive of the UK software group Kognitio, which has responsibility for analysing, among other things, telephone calls made by customers of British Telecom and store purchases that use the Nectar loyalty card of supermarket chain, J Sainsbury.
He says that up to 80 per cent of the price of a new contract can be the cost of cleaning the data – converting, in one case, 15 data types to a single standard.
The Sainsbury contract involves the analysis of the 20bn items purchased in the chain’s stores every nine months – enough, if typed on paper, to make an in-tray pile almost 17kms high.
How can this huge volume of bits and bytes be turned into useful information?
Mr Llewellyn gives the example of skin creams sold to counter stretch marks. Generally bought predominantly by women, if particular stores show high sales volumes, there are likely to be a lot of pregnancies in those areas – an alert for the store manager to stock up on maternity magazines, baby food and clothing.
And if most of the clothing bought is blue, there will be a lot of baby boys in the region: “From buying a jar of stretch cream, I’ve almost got you for life,” Mr Llewellyn beams.
James McGeever, chief financial officer of the US company NetSuite, which markets BI management software, underlines the importance of clean, unambiguous data in breaking down “silos” – data stored in different places and formats within an organisation: “I believe that if the same piece of data exists in two places then one will be wrong.”
The NetSuite answer for its customers is to convert all the data to one consistent type and store it in one repository: “The physical process of loading the data is not as tough as it may sound. It’s actually deciding what data to store there and how to organise your workflows that is the difficult part.”
NetSuite provides executives with tailored “dashboards”, a visual representation of the information important to their jobs.
A well-designed dashboard providing the right amount of pertinent information is a crucial part of BI according to Peter Lumley and Stephen Black of PA Consulting.
They point out that it is often forgotten that managers have limited time to absorb and act on information which, in any case, may be imperfect – if it was perfect, decision making would be no chore at all. A well-designed dashboard can help managers make the best possible decision from incomplete information.
The information, of course, has to be trusted and that is where technology can play an important part – in the automatic roll-up of data to a central repository: “Every time you go through a stage with manual intervention you have the opportunity for time delay and misinterpretation,” Mr Lumley argues.
And these mis-steps are precisely what business intelligence management hopes to avoid.
Copyright The Financial Times Limited 2009. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
The final frontier of business advantage
The final frontier of business advantage
By Alan Cane
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
Business intelligence, information intelligence, business analytics: whatever you call it, all the evidence is that ways of turning a company’s raw data into information that can be used to improve performance and achieve competitive advantage is the topic du jour in many business leaders’ minds.
A survey carried out this year by the US-based consultancy Forrester Research revealed that of more than 1,000 IT decision makers canvassed in North America and Europe, more than two thirds were considering, piloting, implementing or expanding business intelligence (BI) systems.
“Even in these tough economic times, virtually nobody in our surveys says they are retrenching or reducing their business intelligence initiatives,” says Boris Evelson, a principal analyst for Forrester with more than 30 years experience of BI implementation behind him.
What is BI management? It is not about the technical nitty gritty of data warehousing or cleansing technology. While technologies are important – and most are good and effective, according to Mr Evelson – BI management is about ways of systematically making the most of customer information– what it is and what you can do with it.
More prosaically, it is everything that has to be done to raw data before they can be manipulated to facilitate better decision making.
Dashboard that can give a warning light on overspending
Law firm Clifford Chance has found itself learning about habits it never knew it had since analysing its spending trends through an online service provided by Rosslyn Analytics, a boutique software company based in London, writes Dan Ilett.
“It’s very flexible,” says Julien Cranwell, Clifford Chance’s procurement manager. “You can look at your data to reduce spending. We’ve identified opportunities that we wouldn’t have otherwise seen. It’s made us feel a lot more confident of the data we’ve been using.”
The company, which has 29 offices in 20 countries, used a web-based tool called rapidintel.com. The service works like a dashboard with charts and graphs to give an overview of where money has been spent.
“It aggregates and shares information,” says Charles Clark, chief executive of Rosslyn Analytics. “We extract the data in a few hours and categorise them so they go into certain buckets. We then add other data such as credit card or risk information.
“It’s presented as a ready-to-use report. The data cube never changes but they can see it from so many different angles. It’s one view of all company-wide finance, procurement, accounts payable and spend data.”
“Some of the larger areas of spending have been travel, catering and entertainment,” says Mr Cranwell. “It shows where we have varying levels of spending between offices. We are then in a position of power because we know much more about our spending patterns.
“We’ve also looked at a cost recovery programme. Using Rosslyn’s expertise we’re using a module that works on contract management.”
The firm claims to have seen a return on investment of 100 per cent within two months. “The payback period was very fast indeed,” says Mr Cranwell.
It is also about understanding the business and its processes well enough to know what questions should be asked of the data to improve performance.
The basic idea was pioneered more than a decade ago by the US computer manufacturer Teradata, which combined supercomputer performance with sophisticated software to scan and detect trends and patterns in huge volumes of data.
But it was expensive and ahead of its time. Today, high-performance, low-cost computer systems and cheap memory mean that enterprises can and are collecting and storing data in unprecedented amounts.
However, they are struggling to make sense of what they have.
In Mr Evelson’s words: “We have to find the data, we have to extract it, we have to integrate it, we have to map apples to oranges, we have to clean it up, we have to aggregate it, we have to model it and we have to store it in something like a data warehouse.
“We have to understand what kind of metrics we want to track – times, customers, regions and then, and only then, can we start reporting.”
Everybody agrees there is nothing simple about these operations. “It is a very complex endeavour,” says Mr Evelson, “and that is why this market is very immature.”
The business opportunity for BI software has not been lost on IT companies and there has already been significant consolidation in the market, with IBM acquiring, among others, Cognos; SAP buying Business Objects; and Oracle purchasing Hyperion to add BI strings to their respective bows.
Microsoft offers BI software called SharePoint Server and there is considerable interest in open source BI software from younger companies such as Pentaho and Jaspersoft.
IBM alone reckons to have spent $12bn and trained 4,000 consultants over the past few years to develop the tools and knowledge which will encourage intelligence management in its customers.
Ambuj Goyal, who leads the company’s information management initiative, argues that it is a new approach that will “turn the world a little bit upside down”.
“Business efficiency over the past 20 years was all about automating a process – enterprise resource planning [ERP] for example. It generated huge efficiencies for businesses but is no longer a [competitive] differentiator.
“In the past two or three years we have started to look at information as a strategic capital asset for the organisation. This will generate 20, 30 or 40 per cent improvements in the way we run businesses as opposed to the 3 or 5 per cent improvements we achieved before.”
But revolutions are rarely pain-free. According to the Forrester survey: “For many large enterprises, BI remains and will continue to be the ‘last frontier’ of competitive differentiation.
“Unfortunately, as the demand for pervasive and comprehensive BI applications continues to increase, the complexity, cost and effort of large-enterprise BI implementations increases as well.
“As a result, the great examples of successful implementations among Forrester’s clients are outnumbered by the volume of underperforming BI environments.”
In fact, more than two thirds of users questioned said they found BI applications hard or very hard to learn, navigate and use.
The business case for BI management is not helped by the difficulty of making a strong case for return on investment.
It is, for example, hard to decide which tools and processes should be included in the assessment – Microsoft’s SharePoint is much more than a BI tool, for example, but separating out which strands are contributing to improved revenues and which are not is a challenge.
As Mr Evelson notes: “The grey boundary lines around which process and tools to include, the multiple BI components that typically need to be customised and integrated, and the frequent unpredictability of BI system integration efforts all make BI business cases an effort not for the faint of heart.”
How, then, should executives think about business intelligence management? Royce Bell, information management specialist with the consultancy Accenture takes a robustly pragmatic view: “Business is made up of processes. Some of them may interact with the outside world, but there is a definite chain of events.
“All that business intelligence is supposed to inform, is any decision along that chain of events. The question an executive should be asking is: ‘At this point in the chain, what information do I need?’.
“Going through each and every one of your processes to be able to ask that question is hard. People are disappointed because they haven’t been able to get wisdom simply by piling all the data in one place.
“That [data warehousing and mining] sounds more exciting and more fun than going through your processes to determine what you need.”
Mr Bell believes that many executives are suspicious of the quality of the information provided by BI software: they think the data are “rubbish”, and there is no doubt that transforming data into intelligence requires clean data.
Roger Llewellyn is chief executive of the UK software group Kognitio, which has responsibility for analysing, among other things, telephone calls made by customers of British Telecom and store purchases that use the Nectar loyalty card of supermarket chain, J Sainsbury.
He says that up to 80 per cent of the price of a new contract can be the cost of cleaning the data – converting, in one case, 15 data types to a single standard.
The Sainsbury contract involves the analysis of the 20bn items purchased in the chain’s stores every nine months – enough, if typed on paper, to make an in-tray pile almost 17kms high.
How can this huge volume of bits and bytes be turned into useful information?
Mr Llewellyn gives the example of skin creams sold to counter stretch marks. Generally bought predominantly by women, if particular stores show high sales volumes, there are likely to be a lot of pregnancies in those areas – an alert for the store manager to stock up on maternity magazines, baby food and clothing.
And if most of the clothing bought is blue, there will be a lot of baby boys in the region: “From buying a jar of stretch cream, I’ve almost got you for life,” Mr Llewellyn beams.
James McGeever, chief financial officer of the US company NetSuite, which markets BI management software, underlines the importance of clean, unambiguous data in breaking down “silos” – data stored in different places and formats within an organisation: “I believe that if the same piece of data exists in two places then one will be wrong.”
The NetSuite answer for its customers is to convert all the data to one consistent type and store it in one repository: “The physical process of loading the data is not as tough as it may sound. It’s actually deciding what data to store there and how to organise your workflows that is the difficult part.”
NetSuite provides executives with tailored “dashboards”, a visual representation of the information important to their jobs.
A well-designed dashboard providing the right amount of pertinent information is a crucial part of BI according to Peter Lumley and Stephen Black of PA Consulting.
They point out that it is often forgotten that managers have limited time to absorb and act on information which, in any case, may be imperfect – if it was perfect, decision making would be no chore at all. A well-designed dashboard can help managers make the best possible decision from incomplete information.
The information, of course, has to be trusted and that is where technology can play an important part – in the automatic roll-up of data to a central repository: “Every time you go through a stage with manual intervention you have the opportunity for time delay and misinterpretation,” Mr Lumley argues.
And these mis-steps are precisely what business intelligence management hopes to avoid.
Copyright The Financial Times Limited 2010. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
By Alan Cane
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
Business intelligence, information intelligence, business analytics: whatever you call it, all the evidence is that ways of turning a company’s raw data into information that can be used to improve performance and achieve competitive advantage is the topic du jour in many business leaders’ minds.
A survey carried out this year by the US-based consultancy Forrester Research revealed that of more than 1,000 IT decision makers canvassed in North America and Europe, more than two thirds were considering, piloting, implementing or expanding business intelligence (BI) systems.
“Even in these tough economic times, virtually nobody in our surveys says they are retrenching or reducing their business intelligence initiatives,” says Boris Evelson, a principal analyst for Forrester with more than 30 years experience of BI implementation behind him.
What is BI management? It is not about the technical nitty gritty of data warehousing or cleansing technology. While technologies are important – and most are good and effective, according to Mr Evelson – BI management is about ways of systematically making the most of customer information– what it is and what you can do with it.
More prosaically, it is everything that has to be done to raw data before they can be manipulated to facilitate better decision making.
Dashboard that can give a warning light on overspending
Law firm Clifford Chance has found itself learning about habits it never knew it had since analysing its spending trends through an online service provided by Rosslyn Analytics, a boutique software company based in London, writes Dan Ilett.
“It’s very flexible,” says Julien Cranwell, Clifford Chance’s procurement manager. “You can look at your data to reduce spending. We’ve identified opportunities that we wouldn’t have otherwise seen. It’s made us feel a lot more confident of the data we’ve been using.”
The company, which has 29 offices in 20 countries, used a web-based tool called rapidintel.com. The service works like a dashboard with charts and graphs to give an overview of where money has been spent.
“It aggregates and shares information,” says Charles Clark, chief executive of Rosslyn Analytics. “We extract the data in a few hours and categorise them so they go into certain buckets. We then add other data such as credit card or risk information.
“It’s presented as a ready-to-use report. The data cube never changes but they can see it from so many different angles. It’s one view of all company-wide finance, procurement, accounts payable and spend data.”
“Some of the larger areas of spending have been travel, catering and entertainment,” says Mr Cranwell. “It shows where we have varying levels of spending between offices. We are then in a position of power because we know much more about our spending patterns.
“We’ve also looked at a cost recovery programme. Using Rosslyn’s expertise we’re using a module that works on contract management.”
The firm claims to have seen a return on investment of 100 per cent within two months. “The payback period was very fast indeed,” says Mr Cranwell.
It is also about understanding the business and its processes well enough to know what questions should be asked of the data to improve performance.
The basic idea was pioneered more than a decade ago by the US computer manufacturer Teradata, which combined supercomputer performance with sophisticated software to scan and detect trends and patterns in huge volumes of data.
But it was expensive and ahead of its time. Today, high-performance, low-cost computer systems and cheap memory mean that enterprises can and are collecting and storing data in unprecedented amounts.
However, they are struggling to make sense of what they have.
In Mr Evelson’s words: “We have to find the data, we have to extract it, we have to integrate it, we have to map apples to oranges, we have to clean it up, we have to aggregate it, we have to model it and we have to store it in something like a data warehouse.
“We have to understand what kind of metrics we want to track – times, customers, regions and then, and only then, can we start reporting.”
Everybody agrees there is nothing simple about these operations. “It is a very complex endeavour,” says Mr Evelson, “and that is why this market is very immature.”
The business opportunity for BI software has not been lost on IT companies and there has already been significant consolidation in the market, with IBM acquiring, among others, Cognos; SAP buying Business Objects; and Oracle purchasing Hyperion to add BI strings to their respective bows.
Microsoft offers BI software called SharePoint Server and there is considerable interest in open source BI software from younger companies such as Pentaho and Jaspersoft.
IBM alone reckons to have spent $12bn and trained 4,000 consultants over the past few years to develop the tools and knowledge which will encourage intelligence management in its customers.
Ambuj Goyal, who leads the company’s information management initiative, argues that it is a new approach that will “turn the world a little bit upside down”.
“Business efficiency over the past 20 years was all about automating a process – enterprise resource planning [ERP] for example. It generated huge efficiencies for businesses but is no longer a [competitive] differentiator.
“In the past two or three years we have started to look at information as a strategic capital asset for the organisation. This will generate 20, 30 or 40 per cent improvements in the way we run businesses as opposed to the 3 or 5 per cent improvements we achieved before.”
But revolutions are rarely pain-free. According to the Forrester survey: “For many large enterprises, BI remains and will continue to be the ‘last frontier’ of competitive differentiation.
“Unfortunately, as the demand for pervasive and comprehensive BI applications continues to increase, the complexity, cost and effort of large-enterprise BI implementations increases as well.
“As a result, the great examples of successful implementations among Forrester’s clients are outnumbered by the volume of underperforming BI environments.”
In fact, more than two thirds of users questioned said they found BI applications hard or very hard to learn, navigate and use.
The business case for BI management is not helped by the difficulty of making a strong case for return on investment.
It is, for example, hard to decide which tools and processes should be included in the assessment – Microsoft’s SharePoint is much more than a BI tool, for example, but separating out which strands are contributing to improved revenues and which are not is a challenge.
As Mr Evelson notes: “The grey boundary lines around which process and tools to include, the multiple BI components that typically need to be customised and integrated, and the frequent unpredictability of BI system integration efforts all make BI business cases an effort not for the faint of heart.”
How, then, should executives think about business intelligence management? Royce Bell, information management specialist with the consultancy Accenture takes a robustly pragmatic view: “Business is made up of processes. Some of them may interact with the outside world, but there is a definite chain of events.
“All that business intelligence is supposed to inform, is any decision along that chain of events. The question an executive should be asking is: ‘At this point in the chain, what information do I need?’.
“Going through each and every one of your processes to be able to ask that question is hard. People are disappointed because they haven’t been able to get wisdom simply by piling all the data in one place.
“That [data warehousing and mining] sounds more exciting and more fun than going through your processes to determine what you need.”
Mr Bell believes that many executives are suspicious of the quality of the information provided by BI software: they think the data are “rubbish”, and there is no doubt that transforming data into intelligence requires clean data.
Roger Llewellyn is chief executive of the UK software group Kognitio, which has responsibility for analysing, among other things, telephone calls made by customers of British Telecom and store purchases that use the Nectar loyalty card of supermarket chain, J Sainsbury.
He says that up to 80 per cent of the price of a new contract can be the cost of cleaning the data – converting, in one case, 15 data types to a single standard.
The Sainsbury contract involves the analysis of the 20bn items purchased in the chain’s stores every nine months – enough, if typed on paper, to make an in-tray pile almost 17kms high.
How can this huge volume of bits and bytes be turned into useful information?
Mr Llewellyn gives the example of skin creams sold to counter stretch marks. Generally bought predominantly by women, if particular stores show high sales volumes, there are likely to be a lot of pregnancies in those areas – an alert for the store manager to stock up on maternity magazines, baby food and clothing.
And if most of the clothing bought is blue, there will be a lot of baby boys in the region: “From buying a jar of stretch cream, I’ve almost got you for life,” Mr Llewellyn beams.
James McGeever, chief financial officer of the US company NetSuite, which markets BI management software, underlines the importance of clean, unambiguous data in breaking down “silos” – data stored in different places and formats within an organisation: “I believe that if the same piece of data exists in two places then one will be wrong.”
The NetSuite answer for its customers is to convert all the data to one consistent type and store it in one repository: “The physical process of loading the data is not as tough as it may sound. It’s actually deciding what data to store there and how to organise your workflows that is the difficult part.”
NetSuite provides executives with tailored “dashboards”, a visual representation of the information important to their jobs.
A well-designed dashboard providing the right amount of pertinent information is a crucial part of BI according to Peter Lumley and Stephen Black of PA Consulting.
They point out that it is often forgotten that managers have limited time to absorb and act on information which, in any case, may be imperfect – if it was perfect, decision making would be no chore at all. A well-designed dashboard can help managers make the best possible decision from incomplete information.
The information, of course, has to be trusted and that is where technology can play an important part – in the automatic roll-up of data to a central repository: “Every time you go through a stage with manual intervention you have the opportunity for time delay and misinterpretation,” Mr Lumley argues.
And these mis-steps are precisely what business intelligence management hopes to avoid.
Copyright The Financial Times Limited 2010. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
Resources: Finding a home for all that data
Resources: Finding a home for all that data
By Stephen Pritchard
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
When companies started to build the first enterprise data warehouse and knowledge management systems, in the late 1970s, there was little doubt that these were projects that demanded significant investment in both time and resources.
The early data warehouse systems certainly required mainframe resources, and running queries took days, if not weeks.
But advances in computing power, as well as improvements in programming, have done much to reduce the infrastructure demands of business intelligence (BI). It is now quite possible to run small-scale BI queries using little more than a data source, a laptop computer and a spreadsheet program.
Some businesses – especially smaller ones – do indeed manage their data analysis this way.
However, BI experts caution that this approach struggles to scale up to support the larger enterprise, and can raise real difficulties in areas such as data governance and lead to companies having multiple master data sets, or “multiple versions of the truth”.
“Many people start with something small in scope, and there is nothing wrong with that,” says Jeanne Harris, a BI specialist at Accenture’s Institute for High Performance Business.
“But if marketing, and finance, and sales have their own scorecards, based on their own data, it will be a Tower of Babel. Very few organisations have done a good job of creating a single view of their data.”
Nor is the hardware challenge one that chief information officers – or users of business data – can completely ignore.
Although processing power has increased in line with Moore’s Law and data storage has also fallen in price, the growth of business data is faster still. Volumes of data are reckoned to double every 12 to 18 months, twice as fast as just three years ago.
Some businesses are reacting by moving to grid-based supercomputers, or by offloading BI processing to private or public “clouds”. Others are deploying solid-state hard drives in their data warehouses, because of the superior data throughput they offer.
But such systems are expensive and large organisations, in particular, are beginning to struggle with the time it takes to load data into a warehouse or a BI system, especially if it comes from multiple sources.
“With data warehousing appliances [dedicated computers for data processing], the bottleneck is not the speed of the box or the quantity of storage but the time it takes to load the information, especially if you are dealing with demographic information,” says Bill Hewitt, president and chief executive of Kalido, a data management company.
“Even at data loading rates of 10 gigabytes an hour, there is one company that is looking at 39 weeks to load its data.”
This is leading some companies to consider alternative approaches to analytics, such as stream-based processing. It is also prompting businesses to look at BI tools, as well as broader-based technologies such as enterprise search, that can examine data in situ, rather than require them to be loaded into a warehouse and then processed.
Such technologies could also help businesses to overcome their reliance on data from operational systems, such as customer relationship management or enterprise resource planning. Such transactional data are almost always historic, and leads to BI acting as a “rear view mirror” for management, rather than as an accurate predictor of trends.
“Most organisations don’t use external data but rely on [data from] their operational systems to solve specific problems,” explains Earl Atkinson, a BI expert at PA Consulting Group. As a result, the data will only be as good – and as timely – as the information held in those underlying systems.
Before companies can build enterprise-wide knowledge management or BI systems, they also need to work on the quality of the data. Data can also be accurate but partial, or misleading, especially if they were originally gathered for a different purpose.
“A customer, for example, can exist in multiple IT systems,” points out Tony Young, CIO of Informatica, a data management technology vendor. “You need to have a common agreement on who the customer is, for example, if you want to look at their history.
“If I ask a financial person who the customer is, it is the person you bill. Marketing will say it’s the person who responds to a campaign. For sales it might be the person signing the cheque. These are all correct, but they are not common. You have to agree how you are going to treat that information.”
This, more than hardware assets, network capacity, or even the ability to write complex algorithms to analyse data, goes to the heart of the debate around the resources needed for advanced business intelligence.
Organisations need to decide, early on, which information they are going to use, and be honest about the completeness, or otherwise, of their data sets.
If they do not, the results can be disastrous.
“In the run up to the financial crisis, institutions knew that there were three categories of risk but they only had data for one. So that was the one they thought about,” says Accenture’s Ms Harris. “You need to understand all of the risk variables and how they relate to each other, and this needs different technologies and capabilities in modelling, and in experimental design.”
Organisations also need to consider whether conventional data sources, such as those produced by back-office IT applications, or by more specialist tools, such as a retail point-of-sale system or a supply chain management system, really give the full picture.
Increasingly, companies are looking for ways to mine the information held in “unstructured” data, such as e-mails, presentations and documents, or even video clips or recorded phone calls, to provide a basis for BI, and hence better decision making.
“As much as 80 per cent of the information in a company is unstructured, against just 20 per cent that is structured,” notes Bob Tennant, chief executive at Recommind, a company that specialises in using search technology for information risk management.
“Most business intelligence is focused on that 20 per cent of structured data, as it is pretty high value and easy to deal with. But there are a lot of useful, unstructured data that are not being taken advantage of.”
Tapping into that unstructured information might not be easy. But it is the best, and for some companies, probably the only way to make more use of existing resources, in order to make better business decisions.
..............................................................................................
Q&A: ING Lease UK
ING Lease UK is part of the ING Group – one of the largest financial companies in the world. In 2004, the company acquired three businesses from Abbey National Group.
With 300 employees and 100,000 customers, the company has to ensure its reporting and market perception is as accurate as it can be.
Dan Ilett, for Digital Business, questioned Chris Stamper, chief executive of ING Lease UK, about how it creates useful intelligence from its information.
Digital Business What did you do to improve internal reporting?
Chris Stamper We turned conventional wisdom on its head. We found a tool that allowed the business to assemble all information from disparate data sources into one platform. This allowed us to make decisions in real time.
We ignored the “start small and learn” approach and took the “start big and understand” approach by focusing on the most fundamental question we needed answering which was “where do we make our profit and why?”.
DB What has been your return?
CS As an example, analysis of secondary income opportunity has driven £600,000 ($997,091) of additional annual income.
DB How has using “internal” business intelligence helped?
CS First, it has given us the ability to make decisions based on fact rather than intuition or perception and has provided complete transparency when understanding profit and loss levers.
We have now moved to a “nowhere to hide from the facts” culture, the IT department has been removed from the critical path to information and everyone in the organisation has access to answers. This encourages collaboration and end-to-end thinking.
DB What lessons did you learn from this? What would you tell others to do?
CS That perception-based decision making is a characteristic of sales-led organisations. That culture can be very quickly moved with the right tools and environment.
We now have a strong focus on real data quality.
Copyright The Financial Times Limited 2009. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
By Stephen Pritchard
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
When companies started to build the first enterprise data warehouse and knowledge management systems, in the late 1970s, there was little doubt that these were projects that demanded significant investment in both time and resources.
The early data warehouse systems certainly required mainframe resources, and running queries took days, if not weeks.
But advances in computing power, as well as improvements in programming, have done much to reduce the infrastructure demands of business intelligence (BI). It is now quite possible to run small-scale BI queries using little more than a data source, a laptop computer and a spreadsheet program.
Some businesses – especially smaller ones – do indeed manage their data analysis this way.
However, BI experts caution that this approach struggles to scale up to support the larger enterprise, and can raise real difficulties in areas such as data governance and lead to companies having multiple master data sets, or “multiple versions of the truth”.
“Many people start with something small in scope, and there is nothing wrong with that,” says Jeanne Harris, a BI specialist at Accenture’s Institute for High Performance Business.
“But if marketing, and finance, and sales have their own scorecards, based on their own data, it will be a Tower of Babel. Very few organisations have done a good job of creating a single view of their data.”
Nor is the hardware challenge one that chief information officers – or users of business data – can completely ignore.
Although processing power has increased in line with Moore’s Law and data storage has also fallen in price, the growth of business data is faster still. Volumes of data are reckoned to double every 12 to 18 months, twice as fast as just three years ago.
Some businesses are reacting by moving to grid-based supercomputers, or by offloading BI processing to private or public “clouds”. Others are deploying solid-state hard drives in their data warehouses, because of the superior data throughput they offer.
But such systems are expensive and large organisations, in particular, are beginning to struggle with the time it takes to load data into a warehouse or a BI system, especially if it comes from multiple sources.
“With data warehousing appliances [dedicated computers for data processing], the bottleneck is not the speed of the box or the quantity of storage but the time it takes to load the information, especially if you are dealing with demographic information,” says Bill Hewitt, president and chief executive of Kalido, a data management company.
“Even at data loading rates of 10 gigabytes an hour, there is one company that is looking at 39 weeks to load its data.”
This is leading some companies to consider alternative approaches to analytics, such as stream-based processing. It is also prompting businesses to look at BI tools, as well as broader-based technologies such as enterprise search, that can examine data in situ, rather than require them to be loaded into a warehouse and then processed.
Such technologies could also help businesses to overcome their reliance on data from operational systems, such as customer relationship management or enterprise resource planning. Such transactional data are almost always historic, and leads to BI acting as a “rear view mirror” for management, rather than as an accurate predictor of trends.
“Most organisations don’t use external data but rely on [data from] their operational systems to solve specific problems,” explains Earl Atkinson, a BI expert at PA Consulting Group. As a result, the data will only be as good – and as timely – as the information held in those underlying systems.
Before companies can build enterprise-wide knowledge management or BI systems, they also need to work on the quality of the data. Data can also be accurate but partial, or misleading, especially if they were originally gathered for a different purpose.
“A customer, for example, can exist in multiple IT systems,” points out Tony Young, CIO of Informatica, a data management technology vendor. “You need to have a common agreement on who the customer is, for example, if you want to look at their history.
“If I ask a financial person who the customer is, it is the person you bill. Marketing will say it’s the person who responds to a campaign. For sales it might be the person signing the cheque. These are all correct, but they are not common. You have to agree how you are going to treat that information.”
This, more than hardware assets, network capacity, or even the ability to write complex algorithms to analyse data, goes to the heart of the debate around the resources needed for advanced business intelligence.
Organisations need to decide, early on, which information they are going to use, and be honest about the completeness, or otherwise, of their data sets.
If they do not, the results can be disastrous.
“In the run up to the financial crisis, institutions knew that there were three categories of risk but they only had data for one. So that was the one they thought about,” says Accenture’s Ms Harris. “You need to understand all of the risk variables and how they relate to each other, and this needs different technologies and capabilities in modelling, and in experimental design.”
Organisations also need to consider whether conventional data sources, such as those produced by back-office IT applications, or by more specialist tools, such as a retail point-of-sale system or a supply chain management system, really give the full picture.
Increasingly, companies are looking for ways to mine the information held in “unstructured” data, such as e-mails, presentations and documents, or even video clips or recorded phone calls, to provide a basis for BI, and hence better decision making.
“As much as 80 per cent of the information in a company is unstructured, against just 20 per cent that is structured,” notes Bob Tennant, chief executive at Recommind, a company that specialises in using search technology for information risk management.
“Most business intelligence is focused on that 20 per cent of structured data, as it is pretty high value and easy to deal with. But there are a lot of useful, unstructured data that are not being taken advantage of.”
Tapping into that unstructured information might not be easy. But it is the best, and for some companies, probably the only way to make more use of existing resources, in order to make better business decisions.
..............................................................................................
Q&A: ING Lease UK
ING Lease UK is part of the ING Group – one of the largest financial companies in the world. In 2004, the company acquired three businesses from Abbey National Group.
With 300 employees and 100,000 customers, the company has to ensure its reporting and market perception is as accurate as it can be.
Dan Ilett, for Digital Business, questioned Chris Stamper, chief executive of ING Lease UK, about how it creates useful intelligence from its information.
Digital Business What did you do to improve internal reporting?
Chris Stamper We turned conventional wisdom on its head. We found a tool that allowed the business to assemble all information from disparate data sources into one platform. This allowed us to make decisions in real time.
We ignored the “start small and learn” approach and took the “start big and understand” approach by focusing on the most fundamental question we needed answering which was “where do we make our profit and why?”.
DB What has been your return?
CS As an example, analysis of secondary income opportunity has driven £600,000 ($997,091) of additional annual income.
DB How has using “internal” business intelligence helped?
CS First, it has given us the ability to make decisions based on fact rather than intuition or perception and has provided complete transparency when understanding profit and loss levers.
We have now moved to a “nowhere to hide from the facts” culture, the IT department has been removed from the critical path to information and everyone in the organisation has access to answers. This encourages collaboration and end-to-end thinking.
DB What lessons did you learn from this? What would you tell others to do?
CS That perception-based decision making is a characteristic of sales-led organisations. That culture can be very quickly moved with the right tools and environment.
We now have a strong focus on real data quality.
Copyright The Financial Times Limited 2009. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
Displaying the intelligence: Search goes on for a ‘single view of the truth’
Displaying the intelligence: Search goes on for a ‘single view of the truth’By Ross Tieman
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
The idea that you can keep tabs on how an organisation is performing from a desktop display while also focusing on its strategic direction is hugely appealing.
Every day, many of us do precisely this in a car: the dashboard monitors its systems and speed, while helping the driver safely negotiate the obstacles of a journey. Could similar displays not help in running a company, a sales department, or a group of hospitals?
In theory, they can.
Most industrial processes today are run by mouse-clicks – from nuclear power stations to cloth-cutting machines. Corporate systems store every digit of data created, whether by the sales staff logging their calls, the accounts clerks issuing invoices, the machines doing the manufacturing or the purchasing manager placing orders for materials.
Yet these glorious, information-rich data are so often compartmentalised in fragmented systems, each designed to serve a particular business or organisational function. Bolting them together to turn data into information about corporate or organisational performance can be an IT chief’s nightmare.
It might seem as though a few wires and some simple software could enable data to flow seamlessly between systems, enabling the chief executive to see the basics, such as sales, deliveries, and how much cash the business is using, when they log-on in the morning.
Yet Bill Fuessler, IBM Global Financial Management Lead for business consulting, says this can prove stunningly difficult. “One of the biggest issues is getting commonality of data definition,” he says. “And that problem will last for several years more.”
Standards, and even digital definitions of commonplace business words, may differ in the sales department from those used in marketing, or finance. Combine the data sets, and the “information” simply doesn’t add up. What chief executive would drive a car whose dashboard said it might – or might not – be overheating?
Software companies, however, understand the issues and are working hard on how to extract information from data and reach what Richard Neale, marketing director of SAP BusinessObjects, calls “a single view of the truth”.
For mid-sized companies unencumbered by a long tail of legacy systems and data, or those willing to start again at square one, there are software-as-a-service specialists, such as NetSuite, capable of providing a state-of-the-art system containing every byte of corporate data, fully integrated, on a common set of definitions, accessible at will.
But abstracting information for a corporate, not-for-profit, or even public sector dashboard display is also attainable.
First, you have to discover who wants, or needs, to know what.
In a car there is a speedometer and a fuel gauge, possibly with information on fuel consumption, or distance until you next need to fill the tank. But most of the other dashboard data are displayed only if needed, as an alert – such as when the cooling system fails or a seat-belt is unbuckled.
Business intelligence displays need to follow the same precepts. They have to provide appropriate “mission critical” information for all; to enable users to call up information relevant to their role or task; and to provide appropriate alerts when things go wrong. There is no one-size-fits-all system.
In a car, every driver is engaged in a similar task, but in a company, some users – typically the chief executive or finance chief – need access to a broad range of information, while a departmental head might be interested in particular sub-sets of data. Almost everybody also needs alerts relating to their own areas of responsibility.
That information, as distinct from data, may have to reach them wherever they are. Mr Neale, at SAP, says that increasingly, dashboards are being delivered not just on desktops, but on mobile devices, including smartphones.
The latest generation of SAP BusinessObjects software enables users to have “widgets” on their desktops that highlight particular features of organisational performance.
It can also deliver a sophisticated alert to a smartphone, as a graphic display that enables the user to “mine” the information, calling up detail to establish the nature and cause of the problem to which they are being alerted. An alert could relate to inventory levels, risk, cash balances or even a cost or time over-run on a project.
That list highlights the importance of delivering relevant information to the responsible individual. To be valuable, it has to contain signals that the recipient may need to act upon. The IT boss may need to know if the system is likely to crash, but it’s the finance director who cares about the cash balances, while the IT department overrunning its budget may matter to both.
The desktop remains the presentation location of choice because the size of its display permits a lot of information to be shown.
Historically, many organisations have relied on Excel spreadsheets or Microsoft Office tools to present business information to users.
Today, using modern software, the information can be displayed in the form of gauges, pie-charts, graphs, thermometers, heat-maps – just about any format the user prefers.
What business intelligence data add is the ability to explore the information easily with mouse clicks to discover what happened, where, and why.
A typical NetSuite display is presented on a series of tabs, with pages that might include a meter, top selling items as a bar chart, key performance indicators that provide pop-up graphs, and comparative sales as a chart with variable time-spans. If you have reliable real-time data, you can sort and display it any way you like.
As IBM’s Mr Fuessler says, if a retail company’s sales fall, it is handy to be able to uncover quickly that it happened because of a holiday in Boston that closed three stores, for example, and is not the start of an alarming trend. Inadequate information can lead to false conclusions.
Nigel Rayner, research vice-president at Gartner, says: “When you get the dashboard in, that is when you start to get awkward questions. The chief executive can see revenue is going down, or up, but doesn’t know why. Dashboards are always about reporting. They don’t help you make decisions.”
By definition, dashboards only present current or historic data. But decision-makers want to be able to predict the future. People running large companies, public-sector organisations and even not-for-profits want the IT equivalent of the forward-looking radar that some car-makers have trialled.
As Mr Rayner says: “You need more performance management applications to help people model options.” This is where a lot of corporate IT investment is now going, he says.
But if you are going to start making decisions about business strategy based upon conclusions drawn from computer software you need clean data, and answers to current questions, rather than whatever the system was set up to measure five years ago.
“Most organisations have far too many metrics, without being able to plot cause and effect relationships,” Mr Rayner says. “These are pure business problems, and more technology is not the answer.”
So departmental bosses have to sit down together and agree the questions they want answered, and what they want to measure to get them.
To move from mere dashboards to directing the course of an organisation by drawing on all the information squirreled within its systems, Mr Rayner elaborates a four-stage process. Start by monitoring performance, set up an enterprise metric framework, and add analytic and modelling capabilities with performance management applications. Only then, he says, can you go develop a pattern-based business strategy.
Copyright The Financial Times Limited 2009. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
Published: November 26 2009 18:04 | Last updated: November 26 2009 18:04
The idea that you can keep tabs on how an organisation is performing from a desktop display while also focusing on its strategic direction is hugely appealing.
Every day, many of us do precisely this in a car: the dashboard monitors its systems and speed, while helping the driver safely negotiate the obstacles of a journey. Could similar displays not help in running a company, a sales department, or a group of hospitals?
In theory, they can.
Most industrial processes today are run by mouse-clicks – from nuclear power stations to cloth-cutting machines. Corporate systems store every digit of data created, whether by the sales staff logging their calls, the accounts clerks issuing invoices, the machines doing the manufacturing or the purchasing manager placing orders for materials.
Yet these glorious, information-rich data are so often compartmentalised in fragmented systems, each designed to serve a particular business or organisational function. Bolting them together to turn data into information about corporate or organisational performance can be an IT chief’s nightmare.
It might seem as though a few wires and some simple software could enable data to flow seamlessly between systems, enabling the chief executive to see the basics, such as sales, deliveries, and how much cash the business is using, when they log-on in the morning.
Yet Bill Fuessler, IBM Global Financial Management Lead for business consulting, says this can prove stunningly difficult. “One of the biggest issues is getting commonality of data definition,” he says. “And that problem will last for several years more.”
Standards, and even digital definitions of commonplace business words, may differ in the sales department from those used in marketing, or finance. Combine the data sets, and the “information” simply doesn’t add up. What chief executive would drive a car whose dashboard said it might – or might not – be overheating?
Software companies, however, understand the issues and are working hard on how to extract information from data and reach what Richard Neale, marketing director of SAP BusinessObjects, calls “a single view of the truth”.
For mid-sized companies unencumbered by a long tail of legacy systems and data, or those willing to start again at square one, there are software-as-a-service specialists, such as NetSuite, capable of providing a state-of-the-art system containing every byte of corporate data, fully integrated, on a common set of definitions, accessible at will.
But abstracting information for a corporate, not-for-profit, or even public sector dashboard display is also attainable.
First, you have to discover who wants, or needs, to know what.
In a car there is a speedometer and a fuel gauge, possibly with information on fuel consumption, or distance until you next need to fill the tank. But most of the other dashboard data are displayed only if needed, as an alert – such as when the cooling system fails or a seat-belt is unbuckled.
Business intelligence displays need to follow the same precepts. They have to provide appropriate “mission critical” information for all; to enable users to call up information relevant to their role or task; and to provide appropriate alerts when things go wrong. There is no one-size-fits-all system.
In a car, every driver is engaged in a similar task, but in a company, some users – typically the chief executive or finance chief – need access to a broad range of information, while a departmental head might be interested in particular sub-sets of data. Almost everybody also needs alerts relating to their own areas of responsibility.
That information, as distinct from data, may have to reach them wherever they are. Mr Neale, at SAP, says that increasingly, dashboards are being delivered not just on desktops, but on mobile devices, including smartphones.
The latest generation of SAP BusinessObjects software enables users to have “widgets” on their desktops that highlight particular features of organisational performance.
It can also deliver a sophisticated alert to a smartphone, as a graphic display that enables the user to “mine” the information, calling up detail to establish the nature and cause of the problem to which they are being alerted. An alert could relate to inventory levels, risk, cash balances or even a cost or time over-run on a project.
That list highlights the importance of delivering relevant information to the responsible individual. To be valuable, it has to contain signals that the recipient may need to act upon. The IT boss may need to know if the system is likely to crash, but it’s the finance director who cares about the cash balances, while the IT department overrunning its budget may matter to both.
The desktop remains the presentation location of choice because the size of its display permits a lot of information to be shown.
Historically, many organisations have relied on Excel spreadsheets or Microsoft Office tools to present business information to users.
Today, using modern software, the information can be displayed in the form of gauges, pie-charts, graphs, thermometers, heat-maps – just about any format the user prefers.
What business intelligence data add is the ability to explore the information easily with mouse clicks to discover what happened, where, and why.
A typical NetSuite display is presented on a series of tabs, with pages that might include a meter, top selling items as a bar chart, key performance indicators that provide pop-up graphs, and comparative sales as a chart with variable time-spans. If you have reliable real-time data, you can sort and display it any way you like.
As IBM’s Mr Fuessler says, if a retail company’s sales fall, it is handy to be able to uncover quickly that it happened because of a holiday in Boston that closed three stores, for example, and is not the start of an alarming trend. Inadequate information can lead to false conclusions.
Nigel Rayner, research vice-president at Gartner, says: “When you get the dashboard in, that is when you start to get awkward questions. The chief executive can see revenue is going down, or up, but doesn’t know why. Dashboards are always about reporting. They don’t help you make decisions.”
By definition, dashboards only present current or historic data. But decision-makers want to be able to predict the future. People running large companies, public-sector organisations and even not-for-profits want the IT equivalent of the forward-looking radar that some car-makers have trialled.
As Mr Rayner says: “You need more performance management applications to help people model options.” This is where a lot of corporate IT investment is now going, he says.
But if you are going to start making decisions about business strategy based upon conclusions drawn from computer software you need clean data, and answers to current questions, rather than whatever the system was set up to measure five years ago.
“Most organisations have far too many metrics, without being able to plot cause and effect relationships,” Mr Rayner says. “These are pure business problems, and more technology is not the answer.”
So departmental bosses have to sit down together and agree the questions they want answered, and what they want to measure to get them.
To move from mere dashboards to directing the course of an organisation by drawing on all the information squirreled within its systems, Mr Rayner elaborates a four-stage process. Start by monitoring performance, set up an enterprise metric framework, and add analytic and modelling capabilities with performance management applications. Only then, he says, can you go develop a pattern-based business strategy.
Copyright The Financial Times Limited 2009. Print a single copy of this article for personal use. Contact us if you wish to print more to distribute to others.
Subscribe to:
Posts (Atom)