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Two Converging Trends for Software as a Service Business Intelligence

Originally published abril 9, 2009

Two Converging Trends

Acquiring business intelligence (BI) capabilities through a software-as-a-service (SaaS) model versus enterprise business intelligence represents the inflection point of two separate trends in business.  One trend signals the increasing importance of gaining insight into all manner of business events. These events encompass not just transactions, but patterns in activity as widespread as customer responsiveness, network management, supply chain performance, and fraud detection. The focus on business intelligence comes from business grasping the importance of the axiom: “If you can't measure it, you can’t manage it.”

The second trend relates to an increasing interest in the concept of SaaS. The idea of leasing rather than buying a software application, and accessing it over the Internet, offers companies many benefits relating to the conservation of resources. With a SaaS application, companies can generally:

  • Deploy applications faster (weeks rather than months)

  • Reduce the cost of deployment (by a factor of four)

  • Avoid the cost of hardware and associated maintenance and monitoring

  • Eliminate the need for on-site expertise in the application itself

These two trends are converging now for a variety of reasons. Not the least of these is the realization that overarching business insight relies on the integration of information from a multitude of systems. Even companies that have standardized on all-encompassing enterprise resource planning (ERP) applications realize that sometimes key business data exists beyond the boundaries of such applications. While ERP vendors are concertedly designing and acquiring new modules, two facts remain: it takes time to incorporate new and acquired modules into the ERP infrastructure, and companies may have custom-built modules whose functionality outweighs the promises and even the reality of what ERP vendors provide. 

A Plethora of Data Sources

At the same time, companies growing through acquisition frequently find themselves saddled with a plethora of data sources. One user of SaaS-based business intelligence revealed his division (not even the entire company) extracted data from eight different ERP systems.

Our assessment: In order to derive value from customers or employees or data gained after an acquisition, companies must find a way to integrate it quickly.

This begs the question: Isn’t this integration the responsibility of a company’s information technology (IT) department? The answer reveals a key conundrum facing line-of-business (LOB) executives who require BI capabilities for performance-based decision-support such as sales and profitability. Even while they require a perspective that can only come from the integration of multiple data sources within the company, IT’s increasing importance to the viability of all phases of the company — not just any individual LOB — means that its staff is increasingly focused on projects that provide the biggest payback for the company as a whole. This is not to say that LOB projects are ignored, but according to our research, IT frequently assigns them a lower priority. Even as the LOB is under pressure to deliver results, BI projects can take up to six months when there are limited IT resources to go around. Our case study on a $10 billion manufacturing company is a prime example of this.

In the meantime, employees still need to analyze data. Frequently, they will revert to using a spreadsheet, an application about which they have a high level of comfort. While this gives employees limited insights, it eliminates the opportunity to gain visibility into a wide swatch of corporate trends. Because they tend to proliferate throughout a company, frequently containing inconsistent data, spreadsheets fall short of providing the ultimate goal that companies need for reliable business intelligence: a single version of the truth.

In response, LOB executives are increasingly turning to SaaS-based BI vendors for a variety of reasons:

Expertise in data integration: Making data consistent known as the process of normalization and rationalization is a difficult process. For SaaS BI vendors, this is a key core competency that saves time for companies.

Pre-built templates and dashboards: For midsize companies, which typically have fewer IT resources than large enterprises1, SaaS BI vendors can provide pre-built reports that highlight basic corporate needs e.g., sales and profitability, segmented by region, channel, salesperson, product, or stock-keeping units (SKUs). (SaaS BI vendors also offer consulting services at additional fees to develop specialized reports.)

Reduced risk: Companies that tackle internal BI deployments bear more risk than if they hire another firm to do it. With internal budget restrictions, companies may end up with fewer features than they want. With SaaS business intelligence, the external vendor bears the risk.

Reduced cost: An internal BI deployment requires up-front capital expenditures of both hardware and software. The latter includes not only the BI software itself, but licenses for software that migrates data from one database to another, such as ETL (extract, transform, and load) software, or data integration hubs combined with data quality or profiling software for synchronization.2  Companies using a SaaS BI vendor pay monthly or annual fees. From a budgeting standpoint, a SaaS BI solution offers a repeatable yet predictable business expense.

Improvements in security: While some companies initially shied away from allowing corporate data to be transferred outside its secure firewalls, advances in data security including secure FTP and data encryption abrogate those concerns.

Specific Vertical Uses of SaaS Business Intelligence

According to our research, theses four industries are where SaaS business intelligence has strongest foothold:

Financial Services: As in many industries, these companies use SaaS business intelligence for marketing purposes: conducting demographic profiling to determine the most likely households for credit card offers, for instance. In the insurance industry, insurers are beginning to make hosted BI systems available to their agents so that they can easily discern their own sales and demographic trends.

Healthcare: Segments using SaaS business intelligence in this industry range from insurance payers to pharmaceutical companies. Business intelligence is utilized in marketing efforts to determine the best promotions based on factors such as demographics and deductibles (see the Blue Cross and Blue Shield of Florida case study). Pharmaceutical companies use SaaS business intelligence as well to determine the validity of marketing programs (see the McKesson case study).

Manufacturing: On-demand BI usage spans a wide range of activities in manufacturing – especially within complex supply and demand chain management processes . Manufacturers use dashboards and performance metrics to track multiple facets of deliveries from suppliers: did the agreed-upon number of widgets arrive at the proper warehouse on a timely basis, and did they meet quality standards? Is the company getting a higher rate of returns (or customer support requests) than normal on particular products? Other performance metrics are used for operational decision-support such as, “Are some products lasting so long that the company should increase the length of their warranties as a marketing differentiator?” (For more on manufacturing, see the Welch’s case study.)

Retail: The diversity of stock-keeping units makes retail and merchandising a rich lode for SaaS business intelligence. Retailers routinely parse sales data in order to better determine what will sell in the future. For instance, does a particular color or size sell more than another? Do particular colors sell better in one season or region than another? (For more on retail, see the Car Toys case study.)

Our research revealed that companies are using SaaS-based BI software in other, more innovative scenarios. In short, companies exploit low-cost rapid integration and deployment in order to gain insights into either non-traditional or short-term scenarios that they might not otherwise have investigated. For example, a company could measure compliance with contracts or service-level agreements, looking at whether shipments are delivered on time and complete; and if not, is this an anomaly or part of an increasingly common pattern?

Public Sector: Government agencies use geographically based BI tools to monitor data ranging from crime statistics to utilities usage.

Interestingly, we discovered that among SaaS BI vendor Birst’s customers were both churches and casinos. Although each establishment had a unique, non-overlapping customer segment, each is using the service to track similar metrics such as:

  • Number of visitors

  • Reason for attendance or visit

  • Dollar amount spent or donated (tithed)

  • Frequency of visitation

Our Assessment:

  • The software-as-a-service model is converging with increased business intelligence usage.

  • Companies use SaaS business intelligence primarily for sales and marketing analysis.

  • The highest uptake for SaaS business intelligence is in retail, manufacturing, finance and healthcare.

  • The flexibility of SaaS business intelligence is expanding the horizons of usage into innovative areas.

  • Companies must integrate data from multiple legacy sources for the most efficient analysis.

  • The popularity of SaaS business intelligence is driven purely by lower cost, ease of use, rapid deployment and perception of faster time to return on investment.


  1. Large enterprises are defined as having greater than $1 billion in revenues.

  2. Data migration, consolidation and normalization is related to and often considered part of master data management solutions.

Participate in New Survey: Transforming Enterprise Feedback Management into Actionable Customer Insight: Maturity Models & Best Practices

Hypatia's next research study is designed to benchmark the current state of the market, identify best practices and performance metrics used by successful companies to improve performance andprofitability via enterprise feedback management and customer insight initiatives. Survey respondents who complete all applicable questions are eligible to receive a complimentary executive summaryof the report.

How successful are organizations in systematically capturing, managing, analyzing and applying customer intelligence thrhoughout the enterprise? What tangible benefits are realized by those whoinvest in customer knowledge? Our research will benchmark the current state of the market, future plans for selection and investment in technologies or service providers. Moreover, we will assess theprocesses, organizational expertise and key performance indicators that set top performers apart such as:
  • Which team or role is responsible for analyzing and sharing this insight throughout your organization?

  • How effective are various technologies or processes such as: customer experience, enterprise feedback, business intelligence, marketing automation, customer relationship management, web analytics, speech analytics or customer satisfaction in facilitating creation of actionable customer insight?

  • Why do some organizations utilize market research service providers or agencies for customer insight while others prefer to operationalize this process internally?

SOURCE: Two Converging Trends for Software as a Service Business Intelligence

  • Leslie AmentLeslie Ament

    Leslie Ament, Senior Vice President and Principal Analyst at Hypatia Research Group is a customer intelligence management thought-leader and industry analyst who focuses on the business value of technology in regards to how organizations capture, manage, analyze and apply actionable customer insight to improve customer management techniques, reduce operating expenses and to accelerate corporate growth. Her research and advisory services include: Customer Analytics & Interaction, Advanced Analytics, Business Intelligence and Big Data Analytics, Social Media Intelligence/Text Analytics, CRM, Digital Marketing Automation, Customer Data Management/Data Quality and Governance, Risk & Compliance.

    Editor's Note: More articles and resources are available in Leslie Ament's BeyeNETWORK Expert Channel on Customer Analytics & Insight. Be sure to visit today!

  • Howard BaldwinHoward Baldwin
    Howard is a Senior Analyst, Enterprise Information Management and Data Quality, with Hypatia Research. Since 1987, Howard has covered the impact of technology on business, writing about everything from PCs and Macintoshes to games and mainframes, and the chips that run them. With extensive expertise at leading industry publications including Electronic Business, Electronics Design Chain, ZDNet Tech, M-Business, Line56, PC Computing, Corporate Computing, UnixWorld, Open Systems Today, Macworld, CIO, and Upside, Baldwin's work as executive editor, senior editor, columnist and author has significantly influenced and educated business leaders for over two decades. In the book publishing industry, Baldwin co-authored Teach Yourself Macintosh in 24 Hours (with Anita Epler; Hayden Books, 1999) and edited Mac OS X for Unix (by Matisse Enzer, Peachpit Press, 2002). He is also the author of Quip City (Robert D. Reed Publishers, 2004).

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