Get smart! 3 steps to better Business Intelligence

Businesses today are continually asking how to cut expenses and improve profitability. Increasingly, a comprehensive Business Intelligence solution is the tool they’re turning to for answers – David McNickel finds out how it’s done...

So what exactly is Business Intelligence (BI)? Although the concept of BI can be fairly daunting – conjuring up images of giant computer banks and legions of tech-staff – in reality it can be summed up in a sentence. Business Intelligence is nothing more than the process of increasing a business’s competitive advantage by the intelligent use of available data in decision making. To use a medical analogy, if information is the corporate lifeblood – then you need to know how healthy you are and weigh up your vital signs against your competitors.

Like many ebusiness related solutions, the implementation and technology costs of BI have meant that in the past it has been the exclusive domain of big businesses. More recently, however, software costs and development times have come down significantly – making BI an affordable option for many small to medium-sized organisations.

Goodbye to gut feel
So what does BI have to offer? According to a recent survey in Business Week magazine a staggering 60 percent of managers used ‘gut feel’ to make decisions more than 50 percent of the time. And 77 percent of respondents said they were aware of bad decisions managers had made because of insufficient information.

While the ramifications of these mistakes are usually plain to see, what’s less obvious is how they impact on an organisation’s ability to grow – and grow profitably. In his book, Mastering the Rockefeller Habits, US-based ‘growth guru’ Verne Harnish describes a series of evolutionary stages in the growth of an organisation from a small firm to a large company, and the barriers to be overcome to leap from one stage to another. Harnish says once an organisation hits 50 employees and up (which under US conditions equates to revenue of around US$10 million to $50 million), then typically all its information systems need to be upgraded.

“When you go from two employees to ten, you need better phone systems and more structured space. If your company goes to 50 employees, you still need space and phones, but suddenly you need an accounting system that shows more precisely whether, which, and how projects are actually making money.” Above US$50 million revenue and he says they need to be revamped again, as the organisation tries to tie all systems to one database of customers and employees. When a company grows beyond this point, Harnish says it’s expected to have enough experience in the marketplace that it can accurately predict its own profitability.

Profitability has of course been important all along the way but at this stage it becomes critical to predict more precisely, since small percentage swings either way can represent millions of dollars – and a growing business will typically hit a Business Intelligence crunch point when managers realise they can’t give stakeholders, shareholders or directors, performance predictions, because they can’t get usable information from their data systems.

“The fundamental journey of a growing business is to create a predictable engine for generating wealth as it creates products and services that satisfy customer needs and creates an environment that attracts top talent,” Harnish says.

“By revealing patterns that would otherwise lie hidden in data, BI systems help managers make the right decisions that lead to growth as well – as they make sense of the sheer scale of an operation once that growth has been achieved.”

Once all the BI ‘pieces’ are in place, including a standardised infrastructure, databases that talk to each other, real-time document conversion, storage and management software, companies begin to create what may best be described as a ‘corporate memory’. Business intelligence tools are then used to dig through this information – revealing patterns and relationships within the business activity and history. Management reports based on this type of analysis can help organisations with their strategic and competitive positioning.

The benefits may include identifying who the best and worst customers are, which products make the most or least profits, fine-tuning of marketing or pricing policies, the retention of customers and predicting market trends.

Which BI solution?
There are a range of Business Intelligence tools and solutions in the Australian market, some home grown, some from the United States, and some from Europe. ERP and database vendors also package business intelligence tools into their suites, but the usual dynamics of best-of-breed versus suite apply – specialist vendors are often able to create a better match for an individual business, rather than a solution which may be just ‘okay’.

Vendors say it’s the ability to draw information from the entire range of an organisation’s data sources, as opposed to just what exists in an ERP database that sets standalone BI solutions apart from ones that come as part of an ERP suite. “Most organisations have data in sources other than the core ERP systems,” says SAS solutions manager Greg Wood.

“These include other operational databases, CRM systems, legacy sources and external data sources - all of which ERP systems aren’t well suited to integrating into the decision making process. A standalone BI solution leads over ERP suites in integrating data from multiple sources and thus the improvement of data quality.” At Cognos, marketing director David Merchant agrees. “When BI comes integrated in a particular ERP solution then it’s typically limited to reporting off that solution and has limitations around what external data can be included. So if an HR person wants to see a simple report, such as revenue per employee, and their HR data is separate to their GL/ERP solution then that simple requirement becomes a major challenge. Cognos BI incorporates all data from all sources.”

In general terms the BI process is made up of three components or ‘steps’.

Step 1: collect the data
Technological advances have made it possible for businesses to gather and store huge amounts of data about their day to day activities.

Flowing in from numerous sources, this data typically includes customer contact, financial information, operations and transactional data.

In order to be any use at all in a BI sense, however, it must all be captured electronically – warehouses full of paper files are of little use.

Typically, when approaching a BI solution, most companies find that over the years they’ve built up a number of disparate legacy systems and databases – some Oracle here, some IBM there.

Routinely these systems aren’t integrated and they may be difficult to extract information from. It is at this stage of the process that it becomes clear that ‘data’ and ‘information’ are two different things – and data on its own is not enough to make decisions.

The good news is that most modern BI software can make use of legacy information stored in these disparate systems, meaning old databases don’t necessarily have to be replaced. The technical term for this process is to perform an ETL function – which is to Extract, Transform and Load data. On a continuing basis, BI applications extract data from databases or transaction systems, check it for errors, clean it up and translate it into a uniform format.

Step 2: data analysis
This is the crunch stage of a Business Intelligence solution – the raw data is coal – and you’re looking for diamonds. Once again, although the thought of getting useable Business Intelligence from a collection of disparate databases and applications may seem daunting, the process is actually relatively easy. The first step to take in the Data Analysis stage, is to decide exactly what it is you (and your staff) need to know. Essentially this boils down to what are the key business decision needs for your company.

What questions do managers need answered – and how do they know whether performance is improving or declining? Of course for different department heads the informational needs will be different. Sales people want sales and marketing info, production people want volume estimates, while customer service managers want the facts about their company’s relationship with its customers. A BI system needs to filter data into information that’s relevant to decision makers and it should also present the information in a way that’s easy for them to review.

Many BI systems allow users to view data in a variety of different formats including tables, charts and graphs. These are often referred to as ‘Dashboards’ and they use an organisation’s data to present managers with clear, actionable information in a highly graphical, intuitive format – making smart decision making easier. These BI tools help knowledge workers understand and use information in ways they might never have previously considered – including the creation of many ‘what if?’ and best-case/worst-case scenarios.

But that’s only if they use them. Research has shown that everybody absorbs information differently. Some people learn best with graphics, while others respond to text or numbers. You need to understand how your knowledge workers like their info presented. A BI solution that nobody likes using could potentially be a waste of money.

The basics

As a starting point, a Business Intelligence solution should provide the following;

1. Fundamental analysis tools so staff can do what they already do with existing spreadsheets or other methods.

2. Insight into your company’s performance that would be difficult or impossible with your current tools.

3. Analysis that goes beyond the surface, so staff can look behind the numbers to get to the source of a problem.

4. Information delivered in context so that any reasonably intelligent person could make an informed decision.

5. The facility to produce reports automatically so that information can reach people when they need it.

Step 3: take action
Unfortunately Business Intelligence has no intrinsic value until it is used. In simple terms, knowledge workers using their organisation’s BI systems must feel empowered to make decisions – and take action accordingly. In many respects this step of the process should be carefully considered at the outset of BI development, as the only truly successful BI implementation is one with complete senior management buy in.

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