A rapidly growing business model, software as a service (SaaS) has many advantages over the typical enterprise software approach. Unlike applications that need to be installed and maintained internally in a company's environment, SaaS applications are accessed by the company's business users over the Internet through a browser.

The benefits of the SaaS model are plentiful - from no required purchase of hardware, to lower IT requirements both for installation and maintenance, to the significantly lower implementation, maintenance and entry costs.

The outstanding success story of SaaS has been Salesforce.com. Salesforce has made customer relationship management (CRM) affordable for small and mid-sized businesses (SMBs), as well as forging inroads into large companies as a replacement for standard enterprise CRM systems. With such an attractive business model and widespread adoption well underway, why is it that enterprise applications across the board and, particularly BI, have not yet moved to the SaaS approach?

First of all, BI tools have been designed and priced primarily for large corporations rather than for the SMB market. The breadth and amount of data in a large organization makes it a much more suitable target for BI to help improve corporate performance. There is less need for a BI tool or application in the SMB market. No new or existing BI company has, until recently, pushed forward to provide a SaaS solution for BI in the large corporate market in the way that Salesforce.com did with CRM in the SMB market.

Another issue that has hindered the growth of BI as a service has been the reluctance for companies to allow sensitive data to reside offsite. BI tools are frequently used to manipulate company financial data, so until relatively recently there has been a strong aversion to letting this data go off company premises. Rightly or wrongly, companies have felt that their data was less secure outside their own four walls.

Finally, as opposed to an application like CRM, which is used by whole teams within a company, BI tools tend to be used by specialists to generate reports for their internal customers within the company - finance, marketing and sales and more. The concentration of BI users at corporate headquarters presents less need for a SaaS application than the geographic distribution of sales and marketing personnel, who are the primary users of CRM.

The Complexities Involved

System performance. Because BI has traditionally taken the form of a tool that can be used for analyzing many different types of data, there is always a greater possibility of performance issues given the amount of data that might be accessed. It is vitally important that performance times for a BI application running over the Web are acceptable.

Given the even greater sensitivity associated with financial information (which is frequently analyzed with BI tools), security, not only in data storage but also in data transfer is essential.

System uptime. As with any application used to run the company's business, system uptime must be as close to 100 percent as possible. Any downtime could prevent decision-making that could have a significant impact on company financial performance. A BI SaaS application must be practically always available.

En suring data quality. Since an outside vendor is managing the application rather than the company itself, it is critical that the data used in the BI SaaS application be even better screened than it might be for an internal application. It is a subtle point, but there is a handoff of the data and so it is essential to ensure its accuracy so that the results generated by the BI SaaS application have validity.

Best Practices

Provide customization at setup. Each company has its own terminology, not only for its products, but also for generic items such as accounting and production terms. Companies will have their own favored units of measure and, of course, languages and currencies for international operations. It is important that a BI SaaS application be set up with a company's specific terminology so that users can interact with the system efficiently.

Make the BI SaaS System easily used by non-BI experts. Many BI tools are complex to use and often rely on specific personnel to generate the reports that functional groups such as sales and marketing might want. It is highly desirable that the BI SaaS application be designed such that business users in the different departments can use this system easily after a modest investment in training.

Provide flexibility for business users to create their own reports. Along with making the BI service application easy for the business user to operate, it is critical that such a user is able to create his or her own reports easily. A manager might want a report showing the profitability of a certain set of products in a single geographic region for a specific sales region. Being able to instantly create this makes the company much more nimble in responding to changes in the market and competitive moves.

Use a state-of-the-art data center and secure socket layer. Data security is absolutely essential. Companies were very nervous about letting critical information reside outside their facilities. However, with the sophistication available nowadays with secure data centers that are SAS 70-compliant, data may be more secure when hosted offsite than it is on the company's own premises. Data transfer should be done over FTP with SSL 128-bit encryption to provide maximum data transfer security.

Provide an individual server for each instance of the application. With the very high sensitivity of financial data frequently analyzed with BI systems, it is essential that a company's data be stored by the BI SaaS vendor as single instance of a database, running on its own server rather than sharing resources with another company's data. This requirement goes beyond what might be acceptable for a CRM system operating in SaaS mode.

From a Tool to an Application

The move toward BI as a service is being accelerated by the emergence of BI applications and their appeal to a broader range of users. A relational database could be thought of as a tool and a CRM software package (based on a database) as an application directed to particular business area. Similarly, differing from BI tools with their horizontal focus, BI applications are now emerging that target individual business challenges.

Consider the challenge for a manufacturing company that makes hundreds or thousands of products, sells them to perhaps hundreds of customers and produces them on multiple production lines in various plants. Many manufacturers have long known the importance of considering production speeds as well as margin per unit when analyzing the profitability of individual products. However, there has been no BI application to date capable of combining the margin and production run-rate data for such a complex combination of products, customers and production facilities. Furthermore, while existing BI tools might be able to perform some historical analysis after a significant investment in data organization and manipulation, certainly none could perform simple, rapid what-if analysis to model proposed changes in product, customer and asset mix.

Figure 1 is an example of a chart created in minutes by a business user, rather than a BI expert, showing the profitability measured in profit per minute for a selection of a company's products. The rapidly produced, powerful chart quickly lets the business user, perhaps a marketing product manager or a financial analyst, see which products are truly the most profitable and which are poor from a profit-per-minute perspective. By plotting margin against production speed, such a topographical map enables the ability to view profit not just by margin alone but by combining it with the production run rate.

Figure 1: Topographical Profit Map

Based on the chart in Figure 1, the marketing analyst could decide to reduce marketing programs for the product Resin-E-1, which had seemed quite profitable from a margin-only view, and to increase them for Resin-E-2 which, despite its lower margin, generates cash much more quickly. In this case, the marketing analyst accesses the BI SaaS application over the Web and uses it for the very specific goal of profit optimization, the focus of this particular service.

The table in Figure 2 shows data which might be behind a topographical profit map as shown in Figure 1. This table allows the business user to see the exact data used to generate the chart. The user has a range of flexibility in being able to sort by clicking on column headings or by adding, deleting and rearranging columns. Furthermore, the business user could roll up from the Product view to a Product group view, having previously drilled down to the Product view shown in Figure 2.

Figure 2: Data Behind a Topographical Profit Map

Particularly noteworthy in Figure 2 is the portrayal of profitability by return on assets (ROA) at a product level. As opposed to a BI tool which allows a wide range of analysis across all corporate data systems, this particular application was designed to address the mismatch between using margin-only as an operational metric. Margin is a per-unit-based metric whereas company shareholders are interested in overall ROA, which is a measure of profit over time, e.g., per year. Designing an application that calculates profit per minute rather than profit per unit provides an operating metric at a granular level, which is directly related to the shareholder goal of ROA. For the very first time, company personnel can view products or customers by ROA, something virtually unattainable before the advent of a specialized BI application.

To see how a specialized BI application can provide even more value to the business user, consider Figure 3. This table allows the importing of historical data, and the ability of the business user to model changes in volume, prices, production speeds and costs. When a change that can increase cash to the company is determined, this change can be reflected in a new sales plan, operating plan, productivity initiative, price increase or price decrease.

Figure 3: BI Application Deployed in a Service Mode

The BI application deployed in a service mode in Figure 3 thus enables corporate users in sales, marketing, finance and production based anywhere to access the key data over the Web securely and to use it in a timely fashion to make critical day-to-day decisions on products, customers, production facilities and pricing, which will directly impact corporate financial performance.

The Wave of the Future

As companies have implemented more and more systems over the years to capture information such as sales and production data, they are now ready to use this data to address very specific business problems. This reality is now stimulating the move of BI from being a horizontal tool to a set of very targeted applications. As these applications provide enormous value to a wide variety of users across the company (who are thus quite likely geographically dispersed) and because SaaS applications provide very attractive benefits over traditional enterprise software delivery models in general, BI applications as a service will continue to grow strongly in the years to come.

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