You don't need new tools to gain insight into your business -- here are eight ways to make the most of what you've got.
That adage from the Great Depression is making a comeback these days among corporations that are digging deep to maintain profitability using business tools they already have in-house.
One of those companies is Creativity Inc., which found itself two years ago facing a serious threat to its business model.
The company, which designs, markets and distributes crafting products to specialty retailers, was being undercut by overseas manufacturers as retailers began to buy direct. The trend preceded the current economic downturn, but has hit with renewed vigor as the recession has deepened.
"We've been adjusting to a changing landscape," says Jim Mulholland, vice president of IT, and that includes fundamentally changing its product strategy.
To find more profitable, less commodity-driven products, and to cut operating costs, Creativity turned to its existing stable of Cognos business intelligence software. "We made no new purchases at all. We are taking advantage of different parts of the Cognos system, like Event Studio," the Web-based events-management module, Mulholland says.
As the economic downturn puts a strain on revenues -- some of its clients have seen revenue drops of 50% or more, according to Gartner Inc. -- management is leaning on business intelligence (BI) tools like never before.
Nick Millman, senior director for information management services at Accenture, agrees. "The tougher times that some of our clients face have accelerated [a trend toward] getting back to BI and how business can be improved." Executives are using them to find operational savings and to refocus their product lines and strategies, he says.
As business strategies change, business models need to reflect that, says Bill Hostmann, analyst at Gartner. "Deciders need the right information models so they can be effective."
But IT organizations aren't rushing to buy new business intelligence software or build new data warehouses. Instead, they're digging deeper and doing more with existing tools from IBM Cognos, SAS, SAP Business Objects or Microsoft Business Intelligence and other BI vendors. "Organizations are trying to utilize their existing business intelligence tools without going out and buying more hardware and software," Millman says.
Follow these eight tips, say Millman and others who have been down this road, and you too can squeeze more out of your existing tools while giving your business an extra boost.
Consolidate your tools
"Usually people have more tools than they need, and that can be distracting," says Anthony Abbatista, vice president of technology solutions at Allstate Insurance Co. and a former business intelligence consultant. Organizations end up with "different pockets of people doing similar analysis with different tools," and that leads to needless confusion, he says. His recommendation: Consolidate, and be aggressive about it. "Get to the minimum number of tools you need to get the job done."
Over the past few years, Abbatista has overseen the consolidation of 13 data warehouses down to just two and has pushed the organization from a centralized business intelligence analysis and reporting function to a self-service model based on the deployment of customizable dashboards.
Settling on a standardized set of tools was the first step toward empowering business managers and analysts. After a review, Abbatista says the company "killed off" two thirds of the tools in use at the insurer, including redundant products and the "falling stars," yesterday's hot tools that are no longer considered leading edge.
Those efforts paid off before a single new report was created. The business saved on software support and licensing costs, and the simplified tools portfolio made user training on the tools easier.
Standardizing on a single set of tools also facilitated model reuse between different groups. Before, for example, the sales and finance groups had profitability models created in different tools. "If they got different results, you'd spend time trying to rationalize why that was," Abbatista says. Now the process is much more straightforward -- and different business groups can feel confident they're comparing apples to apples.
Let business take the driver's seat
As the downturn continues to reset goals and business strategies, it's more important than ever for companies to make sure that BI technology is being applied to solve the right problems. IT organizations still fall into the trap of putting their technology out front, rather than creating models that respond to changing business needs, says Accenture's Millman.
Work with the business first before developing new information models, he advises. "Start with a clear vision of how information will generate value for the organization," he says. "Think about what business interventions you hope to derive from BI tools. Understand where the business benefit is going to come from, then configure the tools and processes."
At Allstate, two areas of focus are managing loss expense ratios and measuring the effectiveness of the call center. "We've taken experts in the tools and methods and put them together with the business people to find these high-value targets," says Abbatista.
The temptation in larger organizations is to try to do too many things with BI, he observes. Having fewer tools helps with that problem, and management also needs to prioritize what is most important.
"These times have been good because they've brought focus on measuring fewer things well," says Abbatista. At the highest level of the business, Allstate's management is watching 10 or 12 different metrics, he says. While business intelligence tools used by the business units use a wider range of metrics, all of those are designed to support those upstream metrics that management is watching.
New markets call for new data models
Right now, says Gartner's Hostmann, "there's a big strategy change in many organizations from high-value product offerings to low-cost offerings." But businesses that can't compete in the low-cost market must figure out a way to move up the value chain -- and they're using BI tools to get there.
Which is what Creativity Inc. did. To combat the commoditization trend in its core markets, it used the IBM Cognos 8 BI suite to identify and develop high-value products that couldn't be easily commoditized by its low-cost competitors.
It started by purchasing transactional data from retailers in the toy, fashion and apparel segments, adding that data to its existing data warehouse, and analyzing current buying trends. Creativity also uses Smart Software's SmartForecast forecasting software against the data as well.
All that analysis has lead to more "design-oriented, fashion-oriented" products, such as a line of paper dolls based on the popular Project Runway television show.
The strategy appears to be working. Creativity's fashion-based and other unique designs have become the dominant portion of its business -- more than 50% -- and contribute an even greater proportion of its margins, Mulholland reports.
Cost-cutting efforts need to be driven by the business side as well -- another area where creative use of existing BI tools can come into play. "It's important to understand who the more profitable customer segments are, how profitable your products and services are and areas to target for cost savings," Millman says.
Centralize business intelligence
To help find the right areas of focus, Creativity's Mulholland started an analytical center for excellence, a group that includes representatives from different parts of the business, from sales to operations. "You're trying to elevate the IQ of everybody in your company in terms of knowing the key business metrics and measuring them accurately and in a timely way across all areas of the business," he says.
Moving towards that goal, Creativity developed common tool sets and profitability models for its sales and finance groups. Reports are pushed to the desktops and viewed in dashboard applications. From there, Mulholland says, users "can go in and do further analysis."
IBM has been promoting such centers among its Cognos customers as a way to create a standardized set of models across the enterprise using existing business intelligence tools. A common set of BI dashboards developed for one department, for example, can be extended for use with others. In this way, new groups don't have to reinvent the wheel and can get up and running more quickly.
BI tools also are underutilized by role. Business stakeholders may view BI as more of an IT-driven reporting and analysis tool rather than as a business tool. Or the tools may be valued by IT and only one or two other groups, such as finance. As an antidote, "what we've seen is some companies that are looking across business processes and setting up competency centers that start to foster collaboration and dialog across business units," says Anne Milley, director of technology product marketing at SAS.
Put more data in your warehouse
When it comes to data warehouses, the current downturn is a great time for organizations to review what they're tracking and to add more data from business operations into the hopper to find additional savings. Just be very selective about what you add, experts advise.
Milley suggests looking at adding data from call centers, Web logs or other sources. The question companies have to ask in these times, she says, is, "What do I have that I can get [into the data warehouse] at a relatively low cost?"
As sales slowed at Creativity during the downturn, Mulholland and the center for excellence team changed its focus from keeping up with growth to cost cutting. One of those projects involved providing a feedback loop between its back-end ERP system and the CubiScan system it uses for shipping.
CubiScan is a laser-based scanning and weight-measurement system used to ensure that goods are properly packaged to meet customer specifications. (If they're not, the fees can be "considerable," Mulholland says.) While the ERP system issued package instructions with the orders, the standalone CubiScan system wasn't returning data on whether shipments were actually packaged properly -- and many were not. "There was no feedback loop," Mulholland says.
The IT team used the Cognos ETL tool (extraction, transformation and load) to bring the CubiScan data into its data warehouse and then built exception reports for shipments where the margins and tolerances for package dimensions hadn't been met. Mulholland expects the project, currently in deployment, to pay for itself in three to five months.
Make better use of data you already have
In some cases, doing "more with less" may simply be a matter of taking data that users already have and presenting it to them in a more useful way. At the Wisconsin Department of Revenue's Business Intelligence Services Bureau, director Janna Baganz says her organization found a way to present multi-year view of tax data on a single screen. "That proved to be a time-saver," she says.
Her group also worked to combine data from the state's income processing and audit systems, taking the need for exception report analysis out of the user's hands. Now when certain business rules kick out a tax return from the processing system, the staff no longer spends 20 minutes running a manual report on another system and then reviewing it to resolve the issue.
Instead, the integrated systems automatically resolve the problem and process the claim in about two minutes without staff involvement. Since July of 2008, the department has saved approximately 1,750 hours of staff time, says Pat Lashore, administrator for the department's technology services division, and taxpayers who are due a refund now receive it more quickly.
In a similar vein, Allstate has had success pushing report-creation and customization capabilities out to end users through the deployment of dashboards. Previously, the company had a centralized report-writing function within IT, and "it took a lot longer to get answers into the hands of business people," Abbatista says. Now, his team creates dashboards, walks users through the basics of using the tool, and lets them do the rest.
One goal of Allstate's is to build models very quickly with the tools they already have to prove or disprove whether a given hypothesis is any good, he says. If it is, the model will be incorporated in a dashboard and disseminated to staff.
Allstate has institutionalized dashboards to monitor its speed in closing claims and the time to resolve those claims. It wants to drive those numbers down to the point where its performance in these areas becomes a competitive advantage. The self-service environment provided by the dashboards allows managers to monitor their department's performance. They also can add or subtract factors or combine data in different ways to achieve those goals.
Back in the IT department, the self-service BI tools helped Abbatista's team get out of the report-building business and clear out a long backlog of report requests. Through the self-service initiative and a data-warehouse consolidation, he's reduced headcount by two thirds while expanding access to self-service BI tools to 25,000 users within the organization.
Keep your models clean
Make sure you have a clear and consistent data model before you bring new data into your data warehouse or bring in data from another part of the business, and then ensure the new data conforms to your model.
Too often, says Millman, information from different sources or sections of the business gets added to the data warehouse without enough attention to how the existing data is modeled. The result: "It's hard to make sense out of business reports or queries that go across more than one section." For example, financial and customer service data might be modeled in entirely different ways. Accenture, he says, spends a lot of time helping its clients re-architect the way their data is stored.
For Abbatista, re-architecting data also meant rationalizing it for different business uses as new data sources were added. For example, at Allstate, different definitions of the "policy effective date" had to be reconciled before data from different departments could be combined into a single data warehouse for analysis.
IT may also need to allay fears about data quality. If managers don't trust the quality of the underlying data, that can derail their interest in business intelligence projects before they even get started. Mistrust "is like a silent cancer in organizations," says Milley. "Companies are at the mercy of their data quality." Users may suspect that the data is old, or that too many records may be missing data in a given field, such as birth date, she says.
"A common complaint is that the quality of the data isn't good enough," even when it is, agrees Millman. To drive up use of existing BI tools, he recommends producing data-quality dashboards that show just how timely the data is. "It's about crystallizing how good the data quality is and making that visible to the business."
Help users understand the data, not just the tools
Scaling up the number of users who have access to BI tools won't help unless people know how to use them. But that's not the biggest issue when it comes to educating the user. "The trend has been for the front end to get simpler and more intuitive," Millman says. And certainly dashboards have helped in that regard.
"What's often missing is the explanation of where the data comes from and how you can use it to derive some insight," Millman says. For example, the data generated by Creativity's CubiScan system was foreign to business people in the back office. "We have to explain what the data points are and what the data points mean," Mulholland says.
Abbatista focuses on building that knowledge one user at a time. "We build out initial capabilities with front-line managers and people in the trenches. They then become the consultant to people around them."
"It's really [about] teaching people to mine for value," Abbatista sums up. In that respect, he says, "I don't think we'll ever be done with our BI efforts."
Source:Computerworld
