With investment in business intelligence software set to grow across the manufacturing sector, Malcolm Wheatley finds out how companies can harness the full business benefits of their investment
Uxbridge-based industrial coatings manufacturer Trimite faced a quandary. Its IT strategy was clear: an enterprise-wide Sage 1000 ERP system, with Microsoft’s Outlook as the corporate email and workflow tool. The problem lay in figuring out how to access the wealth of highly-specific knowledge held in its legacy Lotus Notes system, particularly its customer-related material. In future, the Sage 1000 customer relationship management module would act as the data repository and search tool – but what about the years and years of information already held in Lotus Notes?
“Almost from the outset, we’d understood that it would be technically impossible to migrate the information to Outlook – it was simply too diverse, and too dispersed,” says Neville Billsom, Trimite IT project manager. “Client visit reports, sample requests, email exchanges with customers, technical discussions: you name it, we had it. And we wanted to keep it – it was simply too valuable to discard.”
The solution came in the form of an enterprise content management application from vendor Datum International, called KnowledgeWorker. While enterprise content management solutions are more usually pressed into service to provide a ‘one stop shop’ so that – for example – price lists and data sheets can be held in a single repository and ‘published’ many times to printed material, websites, transaction engines and ERP systems, their in-built flexibility makes them useful for a variety of other purposes, too.
In particular, says David Webber, channel manager at Stevenage-based Datum, their ability to accept data from widely diverse sources can be leveraged to extract vital data from systems such as Lotus Notes. “Using KnowledgeWorker as a replacement for Lotus Notes isn’t common, but it does happen,” he observes. “When Trimite looked at KnowledgeWorker, they saw that they could use it to index, archive and search years of customer-related data.”
Live since 22 May, the Datum system is already proving a powerful business intelligence tool, says Trimite’s Billson. “It was quite surprising just how much information we had,” he says. “We were finding pieces of information that we didn’t know we possessed.” So powerful is the KnowledgeWorker indexing, archiving and searching functionality, he relates, that a decision has now been taken to use the Datum application’s inbuilt workflow to create information in the first place – rather than merely use the system to access vital insights trapped in an outmoded legacy system.
Writ large, Trimite’s experience typifies many manufacturers’ attitudes to business intelligence. The value is undoubted – if difficult to get a handle on at the outset. But despite the initial uncertainty, the use of business intelligence software is said to be set for rapid growth, as companies strive to gather together data from across their businesses – from shopfloor through to the supply chain – and turn that knowledge into a business advantage.
But just as business intelligence software isn’t cost-free, neither is it risk-free. And the risk isn’t just of diminished value, but actual harm to the business: acting on an answer that is wrong can be worse than not having an answer to act upon at all.
So how can manufacturers avoid the pitfalls posed by a business intelligence project? How, for example, does the company clearly define its intelligence requirements – and then link these with its strategic plan? How, too, can it ensure that the project doesn’t operate in isolation, but delivers analyses and insights to those parts of the business best poised to benefit from them? And how can business intelligence best deliver real lasting value to the manufacturing businesses that invest in it?
One thing that it is important to get right at the outset is the strategic context of a business intelligence initiative, says Richard Wyles, managing director of London-based Paragon Consulting, a specialist business intelligence advisor. “Business intelligence shouldn’t be a technology-driven process, but a benefit-driven process,” he stresses. “There’s a technology aspect to it, certainly, but it shouldn’t be driven by IT – because there’s a danger that the ‘business’ part of business intelligence will get overlooked.”
Likewise, argues Kevin Tingey, European vice president and general manager of aftersales service management Servigistics, in business intelligence, simplicity is a virtue. “Data that doesn’t lead to better decision-making is clutter: companies require the ability to seamlessly drill down from a global overview all the way to individual issues – and within a single system – enabling corrective action to be taken before problems truly escalate,” he stresses. “Business intelligence must be aligned with how people work, whether that means providing a threemonth global summary, or a detailed picture of a single issue: if a system needs configuring to reflect the way that each of us operates, how can it offer the required flexibility moving forward?”
“Manufacturers have been very good at making their operations lean and efficient and focused, but that same focus isn’t always applied to their approach to business intelligence,” agrees Mark Bedford, head of manufacturing business intelligence at data analysis vendor SAS, and a leading supplier of business intelligence solutions. “You’ve got to be absolutely clear about the problem that you’re trying to solve.”
At chemicals manufacturer DSM, for instance, business intelligence software from SAS subsidiary Dataf lux has been retrospectively used for spend analysis in order to drive a strategic sourcing process designed to drive down procurement costs. Deciding that off-the-shelf strategic sourcing software lacked the capabilities that they needed, the company deployed a business intelligence application to go back over five years of purchase data – held on multiple IT systems around the group’s individual businesses – analysing and classifying it into a thousand e- [email protected] commodity codes.
Better still, this information could then be fully-integrated with the normal order-raising process for all future purchase orders around the group – whether they were raised on one of its growing number of SAP ERP systems, or one of the more rudimentary systems in use throughout the group.
“Users enter the text for the item that they’re wanting to buy, along with any items codes that they have, and a screen pops up saying: ‘Here are the top five recommended [email protected] codes, based on what you’ve typed’,” explains Joachim Beurskens, the company’s global data manager. “It looks exactly like the normal SAP purchase order process, but behind the scenes it is matching the text against hundreds of thousands of keywords in several languages, and generating [email protected] codes.”
It’s precisely this sort of pragmatic application of business intelligence software that is lauded by Donald MacCormick, chief transformation officer at London-based business intelligence vendor Business Objects.
“The classic mistake that companies make is to aim too high – building a vast data warehouse to record every transaction, for example,” he warns. “In striving for the perfect set of data, they run the risk of never getting there: better by far to start on a small scale, talking to end users around the business about which information might make a difference to the way that they did their jobs. Think about how business intelligence might add value, rather than thinking of it in terms of reports, tables and data sets.”
Nor need that value lie inside the business: increasingly, manufacturers are turning to business intelligence to inform better decision-making at the interface with suppliers and customers.
Tier one automotive manufacturer ZF Friedrichshafen, a supplier of powertrain and transmission products to a number of major car and truck manufacturers, uses an automotive- specific business intelligence product from Vienna, Austria-based Lixto, for instance. Typically, automotive OEMs ‘publish’ supplierrelated data – quality statistics, transaction data, demand data and so on – to web-based portals, explains Lixto vice-president of product management Marcus Herzog.
“It’s the responsibility of the supplier to go and get the data, and then analyse it,” he says. “It’s not the responsibility of the OEM to provide it pre-analysed.
And with OEMs consistently reducing the number of suppliers that they want to trade with – it’s typically half what it was 10 years ago – the ability to mine this published data for competitive insights is vital.”
Likewise, window coverings manufacturer Hunter Douglas uses an application called Data Integrator from Business Objects to build what is in effect an automated order-entry and acknowledgment system, delivering significant improvements in both service speed and efficiency. “Customers can now submit orders straight into our system and receive order confirmation. Behind the scenes, Data Integrator obtains the data, translates it into XML, validates it and confirms delivery timelines,” says Aart Van Leeuwen, IT business applications manager. It’s not ‘classic’ business intelligence, maybe – but it does add value to both Hunter Douglas and its customers.
And the arrival of ever-cheaper, ever-easier to deploy business intelligence applications will put an end to many standard business excuses, believes John Haigh, head of customer relationship management at Birmingham-based business intelligence vendor and systems integrator CpiO.
“Rather than traditional two-dimensional reports that are inflexible, provide little real business insight, and which promote more management argument than business consensus, business intelligence’s ‘single version of the truth’ can bring about a fundamental transformation of both business understanding and business processes,” he says. “With no need to wait weeks for the IT department to crank out a new report, there is now nowhere for any senior manager to hide.”
It’s a view that isn’t without a certain irony. First enthusiastically embraced by those very senior managers 10 years ago – and almost as quickly discarded as expensive and over-hyped – business intelligence has spent the intervening period in something of a wilderness. Propose a business intelligence project, and you’d better be ready to present senior management with a persuasive argument and a credible ROI.
Its wilderness years over, and with more powerful software combining with a better understanding of how to use that software, the business intelligence market is again motoring. But as managers gain a deeper understanding of their businesses, they can’t expect each insight to come sugar-coated and palatable.