Data Warehouse Enables 30% Annual Growth

When you're a heavily transaction-oriented company selling more than 2 million line items monthly and pride yourself on filling each order to 99% completion within two days, you want to be able to analyze sales figures rapidly, leveraging trends to the most competitive advantage. Silvon DataTracker's business analysis capabilities provided the attraction for ITW Brands (Wood Dale, IL). ITW Brands markets tools and fasteners/fastening systems. It was formed to sell these products to home improvement stores like Home Depot and Lowe's.

For a multinational corporation with more than 365 operating units in 34 countries and revenue approaching $6 billion, ITW's business structure is, to say the least, interesting. The company is decentralized, entrepreneurial, and agile in making decisions quickly. Consequently, the company's philosophy is: "The simpler, the better."

Remaining agile while growing at a rate of 30% a year, meant that the ITW Brands' sales force needed the capability to report a wider variety of sales figures and analyze this data in greater depth. "The problem was we didn't have the right tools available to give our sales people," noted Bob Zitello, ITW Brands' IS manager.

What the sales force had at its disposal, according to Zitello, was a customized order entry/order management business system that contained some sales and analysis reporting capabilities. But it was slow, cumbersome, and terminal-based ("green-screen"). One shortcoming was that users had to dial into ITW's server to access the system. The base data was stored in flat files rather than a database. This meant that analyses required extensive amounts of time just acquiring and organizing the data. Since the business system was unable to address the needs of the sales force properly, Zitello began assessing data warehousing/data mart systems with specific requirements in mind. The new system had to be up and running within a month; it had to provide a smooth interface between the business system and the data warehousing application; and it had to have a point-and-click graphical user interface and remote access.

"At first, we thought we'd go with a customized system," he commented, "but that route was too expensive with too long a time line involved. The other systems we looked at lacked at least one or two of the features we specified - with one exception. That was Silvon's DataTracker Application Data Mart (ADM), which is a focused data warehouse that is application-specific and targets a select group of users." Silvon provides end-to-end business intelligence solutions to manufacturing, wholesale distribution, and retail organizations.

According to Zitello, what set DataTracker apart was a better GUI with its remote extraction capability, which allows users to access the system, physically remove packets of data, and store them in a stand-alone "black box." In addition, Zitello was impressed with the ADM's base views, which allow ITW Brands to predefine a time period such as a month or quarter, and to analyze such data as sales figures between different periods. Another attractive and the most powerful feature was the net change function. "We update our cube - which is a three-dimensional block of data including dollars-customers-ship to over dollars every night," said Zitello. "DataTracker allows us to update only those records that are new, based on a flag in the file. Other systems would have forced us to rebuild the entire cube, which takes a significant amount of time to accomplish."

The Next Step: Implementation
ITW Brands' ADM selection process reflected the corporate tenet for fast decision making. The division started researching data warehousing systems in January, and by the end of March, had signed the necessary agreement with Silvon. Corporate signed off on the paperwork by mid-April. By the end of May, ITW Brands had its first DataTracker data mart up and running. The fact that the IT department knew what the dimensions and structure of the database were going to be contributed to the speedy implementation.

Silvon's manager of corporate support, Paul Dorsett, spent a day with Zitello working out a gameplan. Next, Dorsett sent out a contract consultant to identify where the data was in the existing system that was to go into DataTracker, wrote the software program to extract this information, and tested the load process. This was done in 10 days.

DataTracker's flexibility and scalability has been a plus for ITW in this regard. Initially, the division downloaded only sales information from 1995 to the present in the DataTracker database. Currently, the system has 3,000 ship-to's in the system, reflecting 100 customers. Approximately 80% of ITW Brands' business stems from 20% of its largest customers.

Recently, the division added sales plan information to the database, arming the sales force with such "store-level" knowledge as how many units - with the appropriate dollar amount - must be sold. Next on the agenda is marrying point-of-sale data, which is received from many of the largest customers. This information indicates how many units are going out of customers' doors and will be combined with existing sales data in ITW's database.

The sales department is not the only group experiencing the benefits of DataTracker. The controller's office has also taken advantage of DataTracker's functionality in capturing and storing large amounts of data. According to Zitello, it used to take between two and five days for Brands' to compile and generate the files needed for the sales and analysis report. Now, three hours after the last invoice run, sales figures are available on DataTracker. "If we close the books at 9 p.m. on June 30, the sales people have June's figures first thing on July 1," Zitello noted. "What's more, we recouped our investment in Data Tracker in one year."