Share the Wealth: The Critical Role of Business Intelligence in E-Business
Today’s companies are judged not only on the quality of their products and services, but on how well they share information with customers, employees and business partners. The problem is that all the information people rely on is not in one place. Most organizations have myriad systems, each with their own data sources and presentation mechanisms. This makes maintaining complete, up-to-date information across many departments and business units extremely difficult. The more integrated an enterprise becomes, the easier it is for everyone to get the information they need – so they are empowered to make their best decisions.
The solution depends on technology. And this is where "i-business" is born. The concept of "i-business" refers to an Internet-driven organization that uses information in an intelligent fashion. I-business leverages the ubiquitous network of the Internet to deploy information consistently and accurately, both inside and outside the firm. I-business doesn’t replace e-business. Rather, it is a critical part of an e-business strategy.
The Business Case for Business Intelligence
Every day, more and more people are flocking to the Internet to get information or purchase products. The impact of this phenomenon on business is clear: shrinking profit margins as smart consumers comparison shop with the click of a button, increased competition – some from new or unexpected areas, pressures to make processes more efficient and cost-effective, and surging customer and partner expectations.
The Internet’s global reach and the impact of the search engine have also made people think that getting information should be easy. This is true for everyone from your employees who need information at their fingertips to do their jobs effectively, to customers who will look elsewhere if they don’t easily find the information they need. The bottom line is that the company with the most streamlined operations and the most reliable, useful customer service will become a market leader.
How does business intelligence figure in all this? Business intelligence technology allows organizations to transform data stored in core business systems into meaningful information, which in turn enables you to:
• Know your customer and let your customer know you.
• Streamline your business processes by aligning technology with business goals.
• Know how your business runs as a whole by getting a global, unified view of your organization.
Know Your Customer
The company that provides the best service to its customers is often the company that knows its customers best; which customers are most profitable, which products are most often purchased, the method of payment that is preferred, etc. Having this information lets you analyze your business on the fly, quickly detecting shifts in the market – identifying new patterns in response to a promotion, for example. The goal is to drive closer and closer to a realtime look at customer and sales activity.
On the flip side, you could also say the company that provides the best service to its customers is often the company whose customers know it best. This means creating innovative Internet applications that use legacy data in new, profitable ways. For example, you might want to set up an order-history portfolio for each of your customers, so they can see their own purchasing pattern or even compare it to what others have bought. You can also provide services, such as allowing customers to check if an item is in stock by hooking them from your Web site right into your inventory database. The possibilities are endless – but one thing is clear: To survive, companies must find new ways to leverage the Internet and make it easier for people to do business with them.
E-business has aligned the goals of business and technology more closely than ever before. Companies are now striving to innovate, out-compete and streamline processes using technology. They’re making bold steps into initiatives, such as e-commerce, supply chain automation and customer relationship management. Often, this requires building custom solutions or buying news ones, such as packaged applications. And that results in a technology infrastructure that’s piecemeal, disconnected and difficult to manage.
These stovepipe systems sequester information from one department to another, making it difficult to achieve a panoramic view of the overall workings of the enterprise. You end up with a constantly shifting, disparate environment. Somewhere in there is usable information to help customers make decisions, managers meet quotas, engineers advance the capabilities of the company. The challenge is to simplify the process of getting it and sharing it with people both inside and outside the organization.
To achieve synergy among all these systems, you must be able to directly and quickly integrate new Web applications into your existing corporate data and application mix, so that they can work together seamlessly as one.
Know Your Business
These days, people constantly crave realtime knowledge about their business. Analysts who were formerly satisfied with weekly reports, get impatient if they can’t get 24-hour turnaround. They look at morning data in the afternoon so they can change their strategy slightly for the next morning. This holds true for everyone in the organization. The CEO wants a global realtime view of the entire organization – on demand. Sales managers are concerned with making quotas and growing the business into new regions. Engineers want to access current design specs and supplier information. Support people need to know how products are being used. Shipping clerks need to know which couriers to do business with.
To implement widespread knowledge of the business, you must make it simple for people to access the information they need to help them make better decisions. User preferences are also a factor. People want to see information in a way that makes the most sense to them, whether it’s a spreadsheet, a bar chart, e-mail or a Web browser.
By simplifying the way people get their reports, you open up decision-making to middle-level managers and staff workers throughout an organization. This allows companies to react more quickly to market changes and business problems, instead of having to wait until the situation is filtered to upper-level management and delegated back to the front lines.
No matter how the information is delivered, it must be pulled together and integrated from different places – departments, business units, merger partners and external public sources – and presented as consistent, accurate and reliable information for anyone who needs it.
BI: Then and Now
The traditional definition of business intelligence is technology that allows organizations to transform data stored in core business systems into meaningful information. It lets users query and analyze databases to uncover key issues that affect their businesses, ultimately helping people make better, more informed decisions. Functions like ad hoc reporting, OLAP analysis and data mining provide this capability from different perspectives; that is, they serve the needs of various audiences, from the non-technical business user to the power user.
With the advent of the Internet, BI becomes even more critical because companies have a unified platform for easily distributing information to a wider range of decision makers inside and outside the walls of their organization.
As companies move to implement new systems on the Web, they are gathering more and more data about customers, markets, products and processes – all which can contribute to greater insight and business acuity. And with the nearly infinite reach of the Internet, external data sources become available that can further enhance our decision-making. Add in the wealth of information you’ve accumulated in all your production databases and data warehouses, and you’re sitting on a gold mine.
It is no longer sufficient for a business intelligence tool to access limited types of data. To fulfill the needs of a globally focused organization with disparate data sources, today’s BI solution must be able to access, integrate and cross-reference new data, external data and legacy data. Cross-referencing data in external public sources can increase the value of our own internal data. For example, an insurance company could cross-reference its own data warehouse of insurance rates with the rates of competitors stored in external public sources, to locate areas and markets where they are most effective and those where they are not. This would allow it to customize its marketing programs and adjust its rates to be more competitive.
There is nothing magical about the Internet. It is simply a massive public network, globally accessible and commonly shared. But it has increased the importance and ultimate value of business intelligence technology by providing a foundation for free-flowing information throughout the enterprise and beyond.
Critical Success Factors
The promise of business intelligence today is free-flowing information between disparate systems; between people in different business units; between computers and other devices we use to get our daily information, like e-mail, printers, fax machines and palm computers; between your company and its partners, employees, customers and future customers.
How can you effectively and economically achieve this vision? By creating a flexible BI solution that enables you to:
• Directly access and integrate all your critical data in core business systems, including legacy, relational, warehoused, public and ERP data, without regard to location or format
• Transform that data into valuable information and give it to people in a way that makes sense to them
• Deliver quality information to any audience on demand, enabling organizations to schedule and automatically send critical information to people on a regular basis via Web browsers, printers, fax machines, palm computers and e-mail
Also critical to a successful BI solution is scalability and flexibility, so that as usage grows, the performance of the system is not adversely affected. Plus, to ensure an environment that’s finely tuned and easy to manage and use, a solution should give IT personnel and administrators comprehensive system management tools to help them build, implement, monitor and evolve the infrastructure.
Access and Integrate Data
In today’s enterprise, it is not likely that the data that supports your decision-making is located in one place. Over the years, we’ve built tactical mainframe systems to solve business operational problems, often back-ended by critical legacy data sources. We’ve adopted ERP packages, such as SAP and PeopleSoft, that promised to integrate processes and solve Y2K issues. We’ve created data warehouses in relational databases that provided answers to critical questions. And in some cases, we’ve gone through mergers and acquisitions, introducing a new universe of technology to deal with. All of which results in enterprises with disparate databases on many different platforms.
Companies realize that educated business decisions are not made based on a single data source. For example, a sales force wouldn’t make changes solely based on sales numbers; it would factor in information from human resources, economic indicators, sales figures, and budget and finance reports.
Even though accessing cross-subject information seems logical to many companies, it may not be within their immediate plans – yet, deciding on a business intelligence tool that can support future integration of other data sources is essential for growth. For example, if the sales analysis system you build today can’t integrate data from your legacy HR and customer support databases tomorrow, you may never understand the correlation between increased support staff turnover, customer complaints and the drop in sales the following quarter.
Transform Data into Information
Business intelligence tools like OLAP analysis and ad hoc reporting are appropriate for analysts who understand how to use them. However, all organizations have decision makers who may not be technical enough or have the time to understand these complex tools. In other words, they don’t need to know how the engine works; they just need to push the gas pedal and go. These people need data-driven EIS systems that allow them to navigate data without being a tools expert.
A comprehensive business intelligence solution must provide flexible views of the information for the many different types of users inside and outside the organization, according to skill level and need. Plus, it should allow users to react in realtime by making changes to the data in the core business system that reflects their decision.
Deliver Information on Demand
The world has gone mobile. We’re wireless, connected and free. We all expect information at our fingertips, no matter where we happen to be. A world-class BI solution must provide many ways to deliver information to people. When it comes to building information systems, you need to select one technology that can support all audiences. The maintenance and integration implications of using a different technology for each audience are major cost factors.
In a business world dominated by the Internet, quality business intelligence could not be more important. Succeeding in business depends on how well you know your customers, how well you understand your business processes, and how effectively you run your operations. Without good information and a global view, you will be unable to master any of these three things. And unless you can directly access and integrate your data, transform that data into meaningful information, and then deliver that information the right way to the right people, on demand, you won’t have sufficiently good business intelligence to achieve that mastery.
About the Author: Michael Corcoran is Vice President of Marketing for Information Builders. For more information, visit www.informationbuilders.com.
Eleven Steps to Success in Data Warehousing
By Phillip Blackwood
Although data warehousing has long been an option for big companies, the reduction in warehousing technology costs now makes it practical for smaller companies as well. Turnkey integrated analytical solutions are reducing the cost, time and risk involved in implementation, and corporate portals are making it possible to grant access to hundreds, or thousands, of employees.
1. Recognize that the job is harder than expected. Experts report that 30 percent to 50 percent of the information in a typical database is missing or incorrect. In an operational system that focuses on swiftly and accurately processing current transactions, this may not be noticeable or may even be acceptable. However, it's totally unacceptable in a data warehousing system designed to sort through millions of records in order to identify trends or select customers for a new product. Another challenge is that although database schema changes over the life cycle of a project, historical databases are rarely rebuilt.
2. Understand the data in existing systems. It is important to perform a detailed analysis of the status of all databases that will contribute to the data warehouse. Data interrelationships need to be determined between various systems, and must be maintained as the data is moved into the warehouse. Since the data warehouse implementation often involves making changes to database schema, understanding data relationships among heterogeneous systems is required to predict the impact of any such change, and avoid inconsistencies in other areas of the enterprise.
3. Recognize equivalent entities. One of the most important aspects of preparing for a data warehousing project is identifying equivalent entities and heterogeneous systems. For example, two different divisions may be servicing the same customer, yet have the name entered differently in their records (i.e., "AIG" and "American International Group"). A data transformation product capable of fuzzy matching can be used to identify and correct this and similar problems.
4. Support data quality with metadata. Metadata is data about data; for example, tags that indicate the subject of a World Wide Web document. One major challenge is trying to synchronize the metadata between different vendor products, different functions and different metadata stores. It is important to create and capture metadata for interfaces, business processes and database requirements as soon as possible. Several vendors offer products that have the potential to integrate metadata from disparate sources and begin to establish a central repository that can be used to provide the information needed by both administrators and users.
5. Select the right tools. Data transformation tools extract data, clean it and load it into the data warehouse, while capturing the history of that process. This transformation process may include the creation and population of new fields from the operational data, summarizing data to an appropriate level for analysis, performing error checks to validate data integrity, etc. Look for a tool that can map data from source to target with a point-and-click interface. The ability to track and manage the relationships of interrelated data entities is also useful. Finally, try to find a tool that can capture and store metadata during the conversion process.
6. Leverage external resources. External information sources can increase the value of internal information. Rather than simply comparing yearly sales, use of external data might make it possible to compare sales growth against the increase in the overall market. The integration challenge is even greater when external data sources are involved. In some cases, external data will differ so drastically from existing schema that data transformation algorithms will be required to make use of the external resource.
7. Use information distribution methods. The biggest technological improvements in the data warehousing field have come in the area of information delivery. Today, users can subscribe to regular, personalized reports and have them delivered over e-mail, housing report data securely and economically on the server.
8. Focus on high payback marketing applications. Most of the hot applications in data warehousing involve marketing, because of the potential for an immediate payback in terms of increased revenues. For example, catalog manufacturers are using data warehousing to match specific customer characteristics and customer purchases to target their consumers' needs.
9. Emphasize early wins to build organization support. The availability of a wide range of off-the-shelf solutions has helped to reduce cost and lead-time requirements for data warehousing applications. Off-the-shelf solutions won't complete project objectives, but they can be used to provide short-term point solutions that serve as a training and demonstration platform.
10. Don't underestimate hardware requirements. The hardware requirements for data warehousing database servers are high, due to the large number of CPU cycles required to slice and dice data. Database size also plays a part in server performance requirements. Be sure to select a scalable platform; the typical data warehouse implementation starts out at the departmental level and grows to an enterprisewide solution. Purchasing servers that can be expanded with additional processors is one possible approach. A more ambitious idea is to combine loosely coupled systems that enable the database to be spread out over multiple servers, appearing as a single entity.
11. Consider outsourcing development and maintenance. Most data warehousing applications fit the criteria for a good outsourcing project - a large project that has been defined to the point that it does not require daily interaction between business and development teams. There have been many cases where an outsourcing team is able to make dramatic improvements in a new or existing data warehouse. Typically, these improvements do not stem from an increased level of skill on the part of the outsourcing team, but rather flow from the nature of outsourcing. The outsourcing team brings fresh ideas and perspective to their assignment and can use methods and solutions developed on previous projects.
About the Author: Phillip Blackwood is the Vice President of Data Warehouse and Business Intelligence at Syntel Inc. (Troy, Mich.; www.syntelinc.com).