In This Chapter
Understanding XBRL’s value proposition
Uncovering your own business case for XBRL
Getting guidance on important considerations for XBRL
Solving problems with XBRL
Realizing new possibilities enabled by XBRL
This chapter helps you determine whether XBRL is right for you. Can you make a case for XBRL? After all, you need to see some value, or your life needs to improve in some way in order for you to make a good case for this technology. In this chapter, we help you do just that.
Evaluating Business Use Cases
Business use cases are about justifying why you do something. What value does some new thing add to a business, or how does it solve a problem more effectively or efficiently? If you see economic value, you make a change, which is basic decision-making. Make things more effective and more efficient where you can. You do these things daily so that you can survive as a business. So what exactly does XBRL make more effective? What does XBRL make more efficient? You have to articulate these reasons because they are your business use case — the reason for making use of XBRL.
If you’re in business, you know the many theoretical measurements to evaluate the business case: ROI, present value of future cash flows, net benefit, and more. Fundamentally, all these different approaches measure what is being gained.
Evaluating a business case to determine the gain can be harder than you think because other factors come into play. You have to keep your operational systems running. You may see a positive ROI, but you may not have the cash needed to start a project. Or, perhaps other projects are higher priorities than your project.
Chapter 6 points out the business-information-exchange objectives that we’re generally trying to achieve, a way of measuring the effectiveness of a business information exchange. If you don’t know the objectives, refer to Chapter 6 because you need to keep them in mind when you’re trying to make a business case for XBRL’s use.
Solving a Business Problem with XBRL
XBRL solves the problem of taking information out of one business system and reusing that information within another business system. In many cases, XBRL enables the automation of such exchanges, but XBRL isn’t appropriate for all business-information-exchange situations. In this section, we cover the specific characteristics that XBRL was engineered to provide — XBRL’s sweet spot.
XBRL is a useful tool, but it’s only a tool. You may have heard the saying, “If the only tool you have is a hammer, every problem looks like a nail.” XBRL is a useful collection of open-source technologies, but you definitely shouldn’t use it for every type of problem on the planet!
The creation of XBRL didn’t change the actual business problem XBRL is trying to solve. The problem itself is the same before and after XBRL’s creation. However, XBRL changed the cost/benefit model significantly. Implementations of business systems providing for automated information exchange that were expensive in the past will now cost significantly less. Benefits that were impossible to realize are now not only possible but practical.
XBRL has a sweet spot. Understanding how to access and map XBRL’s capabilities to the business problems you’re trying to solve helps you understand where XBRL can assist you and your organization. If XBRL’s offerings don’t match the desired business outcomes, drive new value in a project, or lower costs, XBRL may not be a good match for your project.
The following list highlights the key areas where XBRL can provide unique value to a business problem. We don’t include things that other technologies, such as XML, provide with the same or similar value. This list reflects what XBRL uniquely brings to the table:
Flexibility within rigid systems: This statement seems like an oxymoron. Extensibility is probably one of the primary values offered by XBRL. We discuss extensibility throughout this topic, pointing out that XBRL isn’t a standard chart of accounts; instead, it’s a dynamic but controlled vocabulary. XBRL isn’t flexible in every direction; it’s flexible in specific needed directions. You can think of this flexibility as XBRL having a specific shape to it. You can’t extend it everywhere, and where you can extend it is known. Yet the notion of a rigid standard of accounts is appealing because it provides something else that’s needed: comparability. XBRL tries to balance these two dynamics: flexibility and rigidity. How you implement XBRL determines where within the spectrum of flexibility and rigidity you choose to be.
Reconfigurable information: The U.S. SEC coined the phrase “interactive data,” trying to explain XBRL in simpler language for the business community. We think interactive information is an even better term. Interactive information means that consumers of information are free to reconfigure information; they’re not constrained by the creator of the information and how that person chooses to present the information. XBRL allows for easy reconfiguration of information.
Rules engine-based validation: Business information is rich with important relationships that are fundamental to create, understand, or otherwise make use of this information. Verification of these relations is key to both the creation and use of the information. XBRL offers an opportunity to use a rules engine-based validation approach that allows for validation of these types of relations. An important characteristic of validation is that you get the capability to check important relations, such as numeric computations (“the total assets must equal the total liabilities plus equity of a balance sheet”) and reportability rules (“if you have inventory on your balance sheet, you need to also have an inventory policy and a specific set of inventory disclosures”).
Another characteristic of rules engine-based validation is that it’s more robust and interoperable than validation implemented programmatically within each individual business system. Further, a rules engine-based approach is much easier for business people to make use of because the complexity is dealt with at the level of the rules engine that extremely highly skilled technical people create. As a result, less technically skilled business people can write good rules without having programming knowledge. Software applications guide business users through the process of creating business rules correctly. The rules engines also allow for better interoperability of applications and therefore even more value because they can exchange, and therefore repurpose, the rules between business software applications.
Clear communication and sharing of rich business-level semantics:
Because XBRL does such a good job of providing for the expression of business meaning needed within XBRL taxonomies, communications between those who write, say, regulations and those who have to understand the regulations can be more clear. Further, those involved in the process, such as software vendors who have to build software, can automate the process of reading the taxonomy metadata to easily update their systems. Finally, both humans and computers can read this standard metadata format. You can use a simple style sheet to change the funny-looking computer readable angle brackets into information readable by humans, just like a Web page or PDF, but computer applications can still read it.
Metadata-driven configuration, no IT involvement required: Business people can easily configure the rich set of metadata, changing business systems dynamically, if necessary. Just as with rules, highly skilled, specialized technical people hide this task’s complexity and build it into business systems. The complexity doesn’t go away; rather, it exists deep within the infrastructure of the system, but hidden from business users. This well-thought-out balance between flexibility and rigidity empowers business users, making them far less reliant on IT help to adjust their systems. So rather than having to write code to reconfigure a system, a business user can simply use a software tool to edit an XBRL taxonomy.
Zero tolerance for errors: Imagine having a math error in a financial statement. That mistake simply can’t happen. Some systems have zero or low tolerance for errors of any kind. You can create robust rules-based system to keep out errors thanks to XBRL’s rigidity (its consistent shape), the rich set of metadata available, and a rules engine that can verify the metadata. Another way to say this same thing is that you can build systems that allow business users to do only the right thing; they simply aren’t allowed to make mistakes.
Don’t read too much into what we’re saying about a computer’s ability to detect errors, though. Computers have limitations as to the types of errors they can detect. A computer can keep out errors only to the extent that a computer system can be told what is an error — basically, to the extent that you can write rules. Also, don’t confuse those mathematical errors with the accuracy of the reported number. Finally, XBRL can’t keep the bad guys from deliberately cooking the topics. So don’t conjure up unrealistic expectations in your mind.
Achieving agreement with exterior parties: XBRL is an easy way to agree with external parties (or even internal parties, for that matter) on two things: a syntax and a metadata set. From a syntax perspective, the advantages of a canonical (standard) approach to, say, integrating business information systems is well understood. XBRL, and in particular, XBRL Global Ledger, is easy for software vendors trying to integrate their systems to have something to agree on. Frankly, many times the syntax makes little or no difference.
A step higher than agreeing on the syntax is agreeing on the metadata set. It’s highly unlikely that two versions of something like the U.S. GAAP XBRL taxonomy will be created. Lots of data aggregators, financial analysts, accountants, and others are already using the U.S. GAAP, including the U.S. SEC. Historically, no one has synchronized these metadata sets, they haven’t been that rich with meaning, and you couldn’t use one standard way to express the metadata. Therefore, everyone created their own set of metadata, and the sets weren’t really that robust because their use was limited. XBRL changes all those things. Creating an XBRL taxonomy, such as the one for U.S. GAAP, is extremely complex and takes thousands of hours for highly skilled accountants and technologists to create. Others will leverage this freely usable intellectual property, creating even more metadata and more synchronization between different business systems. The result is that mashing up data using the XBRL metadata will be trivial.
These specific differentiators help you understand the unique value proposition of XBRL. In Chapter 12, we explain how to achieve these objectives using XBRL. In the next section, we get even more specific and practical regarding who benefits and exactly how.
Gleaning XBRL’s Practical Benefits
In Chapter 3, we explain the general ways XBRL saves you time and money. But you may be wondering about specifics. What’s in XBRL for you? Well, that depends on who you are. The best way to make a case for something is to show, as specifically as possible, the benefits provided. The following groups all benefit from XBRL:
Everyone: Everyone derives these benefits.
Those who specify metadata: Meaning standards setters, legislators, regulators — or anybody else who is articulating some metadata set that others have to report against.
Consumers of information: Those who consume or use information that others have created.
Creators of information: Those who create information that is consumed by others.
It’s rare for someone to be in only one of these categories. Business information exchange is a chain. In some parts of the chain, you may be the creator of information; in others, the consumer; and in others, the one who specifies the metadata.
Benefits to all
Here are the key benefits that everyone derives from using XBRL:
No need to create an individual approach to automated business information exchange: If you’re going to exchange any sort of information, you need to come up with an approach to do so. Each approach has its pros and cons. Some approaches are automatable; others aren’t. XBRL offers an approach that you can use to create an automated information exchange.
Lower cost software: One disadvantage of ad hoc approaches to business information exchange is that you pretty much have to create your own software for the approach you come up with. The more people use a specific approach, generally the more software that exists to support that approach. And the more users, the cheaper the software.
Higher function software: This benefit follows along the same lines as the lower cost of software application. Because XBRL has more users, you generally see more features created for the software because a broader user base funds the creation of the software.
Less errors in information and easier-to-find errors: Because information is structured, automating the process of using the information is easier. The easier it is to automate using the information, the more software can do to help users detect errors in that information. And the more the computer can help you, the less you have to do, such as find and correct errors.
Information communicated with clarity: Because of the formal, standard approach XBRL uses to articulate meaning, understanding the information is easier, which helps everyone involved in a business information exchange stay on the same page.
Readable by both humans and computers: Both humans and computers will be able to read and understand the information, which then allows automated information exchanges and enables computers to use their understanding of the information to provide even more ways humans can use the information. For example, rather than the one fixed format provided today, computers can render information using several different formats. Perhaps the greatest benefits of all may be that after computers universally understand this information, they can crunch the numbers and look for abnormalities in ways that they’ve never been able to in the past. XBRL may not be able to stop people from cooking the topics, but it can certainly help find those who do.
Benefits to those who specify metadata
Those who specify metadata can expect to see these types of benefits:
No need to lock users into an inflexible standard vocabulary: Many times, business users articulate an information set using inflexible standard vocabularies, such as forms, because allowing deviations from the
standard vocabulary is just too complicated. With globally standard XBRL, providing flexibility is easier, so those specifying metadata can allow for more flexibility within their systems, if they need it.
Built-in multilanguage support: XBRL offers a global standard way to provide for the many different languages humans speak around the world. This multilanguage support in itself can be a business case for adopting XBRL. You can author a document in your local language and, with just a click of your mouse, communicate that business information in any language the XBRL taxonomy is translated into.
Leverages standard vocabularies or metadata of others: Because the XBRL standard exists, standard vocabularies or metadata can exist. Before XBRL, there really was no way to agree on one standard way to express a vocabulary. But with XBRL, there is a way: XBRL! Because of XBRL, you can create and use more standard vocabularies, and individual groups don’t have to create their own and usually different (and therefore generally incompatible) vocabularies. You can leverage these standard vocabularies for all sorts of uses.
Benefits to consumers of information
Commonly, it’s thought that consumers of information get the most benefit from XBRL. Creators of information do the hard work of tagging; consumers get the benefit of easily consuming and using the information, or so the perception goes. The examples in the next section clearly dispel this notion, but information consumers still receive significant benefits:
Aggregation: If you’ve ever received information from two or more different people expressing information within a spreadsheet, you’ll understand the problems of aggregating information using spreadsheets. The differently formatted spreadsheets can make extracting information from the spreadsheets challenging. Even if you have a standard spreadsheet format, unintentional errors or misunderstandings in communication always seem to creep up and cause problems with automating information exchanges of this sort. To make spreadsheet-based information exchange work correctly, you have to write a detailed specification for the spreadsheet format.
However, XBRL changes your information exchange options. The specification needed to exchange this information is explicitly documented by XBRL. That is what XBRL is: a specification of how to express this information so that automated processes can be effectively created enabling information exchange. Information exchange includes the process of taking detailed data and aggregating it effectively into summary information without the struggles caused by inconsistently formatted spreadsheets.
Drill down: We mention in the next section that information can be brittle when linking that information is based on the physical location of the information in a spreadsheet cell. Drill down of information is also generally based on location. Drill down is basically the opposite of aggregation. Drill down is the ability to move from the summary numbers down into the detailed numbers that were used to calculate the aggregated total. XBRL solves this issue for drill down exactly the same way that it solves it for aggregation: by specifying a global standard format for the detailed information you’re drilling into.
Flexible information format/set: When you get a set of information from someone, how many times have you wished that you could see the information in some other form? The popularity of spreadsheets and business-intelligence software demonstrates this desire. With XBRL, reformatting information can be as easy dragging and dropping the information contained in an XBRL taxonomy or importing the XBRL instance information into an application of your choice. The presentation information doesn’t hinder this process because it’s separated from the information itself. This flexibility comes from the separation of information and the information’s presentation format.
Not locked into one presentation format: This benefit goes hand in hand with the previous one — you’re not locked into one specific presentation format. If you want, you can export the information easily into PDF, HTML, or a spreadsheet or dump it into relational databases like you’ve never been able to.
Possible to automate comparisons: Because the information is structured and flexible, you can take multiple information sets and easily create comparisons. Because one standard global information format is used, you have to compare lots of information. One reason the comparisons are so easy is because of the standard metadata used by different creators of information. The more standard the metadata, the easier the comparisons will be. Perhaps you want to do a cross-organizational comparison of some sort or a time series of information for one company’s information.
Information is available faster: Information becomes timely because many things are easier and users can automate many processes. Why have the world’s leading stock exchanges and central banks become frontrunners in the area of XBRL? Because by decoupling the information from applications that XBRL provides from their infrastructure, they gain all the benefits of enabling dynamic provisioning with policy-based command and control to deliver available information faster. In other words, they can save millions in IT costs, while gaining millions of new revenues on the business side through gaining insight faster, which results in better risk management.
Benefits to creators of information
Most people see the benefits of XBRL to the information consumers (see preceding section) more clearly than the benefits to information creators. However, creators of information derive significant benefits, too. Along with the general benefits that everybody is privy to, creators of information also get these benefits:
Rules-based creation of information: One of the more significant and exciting benefits of XBRL is the ability to have rules-based information creation. Rules-based information creation means far fewer errors within information and a greater ability to understand what information you’re supposed to report. For example, if rules say that a number in one area needs to be the same value as a number in a different area, a computer process can easily tell you when the two numbers don’t match. Automated validation enables rules-based information creation, guiding you through the process of creating the information as you create it.
Another example is if you create a rule to say that if a value is provided, then you must also include some other set of information as well. These different types of rules make it easier for both those who need to report information to understand exactly what to report and those who consume that information to understand the information they’re using. If you make the information so simple that a computer, which isn’t smart, can understand it, humans will certainly be able to understand the information. Both error detection and interaction or workflow enhancements benefit from these rules.
Aggregation of information: Many times, information comes from many other sources that are aggregated. The aggregated information set is then used to populate a form or a report. You can create sets of spreadsheets that hook the detailed and summary information together, but they tend to be rather brittle as the aggregation is based on the physical location of a number. If a row or column is added, the link breaks. Hooking this information together more solidly by using meaning, which doesn’t change, rather than the physical location, which can change, makes systems that aggregate information far less brittle.
Not locked into a standard controlled vocabulary: Because XBRL is flexible in nature, the need to lock a creator of information into a standard controlled vocabulary (such as a standard chart of accounts) becomes less necessary. As a result, creators of information can better articulate information that might deviate from the norm. This flexibility can make the information more meaningful to those with whom the creators are sharing it.
Increasing Both Reach and Richness
In their topic Blown to Bits (Harvard Business School Press), authors Philip Evans and Thomas Wurster point out that the ubiquitous connectivity of the Web and standards such as XBRL are eliminating the tradeoffs between reach and richness of information and redefining the information channels that link businesses with their customers, suppliers, employees, and other business partners:
‘ Reach refers to the number of people who participate in the sharing of that information. Reach has to do with the quantity of people that you can get to.
Richness refers to the quality of information, as defined by its user and reflected in characteristics of the information such as accuracy, timeliness, flexibility, interactivity, and so on.
Eliminating the historical tradeoffs between reach and richness means that your competitive advantage is up for grabs as your existing competitors and new competitors leverage these new information channels. Complacency on your part can be dangerous and can have disastrous outcomes.
To help give you a better idea of reach and richness, compare the reach and richness offered by a number of mediums. Figure 10-1 shows graphically the relations between the reach and richness of various mediums that were used to distribute information, comparing the reach and richness of each medium.
Figure 10-1:
Looking at the reach and richness of various communication mediums.
The graph in Figure 10-1 shows richness on the vertical axis and reach on the horizontal axis. The line on the graph shows the general relationship between the amount of reach and the amount of richness offered by different mediums for exchanging information. Look more closely at these examples of information distribution systems and how richness and reach were impacted:
Paper before printing: Consider a piece of paper with writing, say created by a monk in the Middle Ages, as the baseline of richness and reach. The monks can write information on paper and distribute the paper. Creating additional copies involves recopying manuscripts by hand. Others can take the paper and distribute it to someone else. To use this mechanism, people had to be able to read, and paper was heavy and therefore limited in reach because it was hard to distribute.
Paper with printing: When the printing press was invented, the richness (what was published) remained about the same; however, printing had a significant impact on reach because now rather than someone having to hand-copy each printed page, they could create more pages. But the cost of a typesetting and printing machine was significant, so few people could afford to produce information in this manner. The photocopy machine reduced the cost of printing, making publishing easier for individuals, which increased reach even more.
Radio: When the radio was invented, information no longer had to be printed at all; it could be transmitted easily to anyone who had an inexpensive radio receiver. Also, targeted information recipients didn’t need to know how to read. However, publishing or broadcasting the radio signal was, and still is, quite expensive.
Television: With the invention of the television, you could now receive not only audio, but also video. This method increased the richness over radio. Still, publishing (broadcasting the audio and video signal) was expensive.
Web: With the invention of the Web, those who wished to publish had seemingly no limitation on either richness or reach. But computer applications couldn’t play in the game because they couldn’t read the information published as most information was published as Web pages for human consumption. As a result, the published information wasn’t very reusable: an example is the mashup, which takes information from various sources, combining it onto one Web page or within one software application.
Semantic Web: With the use of the Semantic Web, reach takes another gigantic leap forward. Now computer systems are also targeted as information consumers. Also, because information is structured for meaning and reusable, it becomes even more useful. Now one information creator can use information others have created with ease.
Today, anyone with Internet access can host a blog and provide any medium and potentially reach everyone on the planet who is connected to the Web for pennies. The point here is that the cost/benefit model has radically changed because both broad reach and deeply rich and reusable information is there to be leveraged. You have a new medium, a new tool, at your disposal. So do your competitors.
XBRL as a New Communication Medium
In 1964, Marshall McLuhan explained the phrase, “The medium is the message,” which he coined to explain how a medium influences how a message is perceived. XBRL is an entirely new medium for communicating a message.
In Chapter 7, we outline many of the different characteristics between paper, electronic paper (such as HTML or PDF) or an electronic spreadsheet, and XBRL. These new characteristics mean new possibilities. Exactly who will leverage these possibilities and how isn’t exactly known today. But we can walk you through one specific, focused example of how you might look at XBRL.
An XBRL taxonomy is a body of knowledge for some domain. The XBRL taxonomy contains the experience, insights, rules, conventions, and other insights and understandings of professionals who have an expertise within that domain. This knowledge is expressed in a form that is readable by both humans and computer software applications.
Because this professional domain knowledge can be effectively articulated in a form understandable by humans and computers, two interesting things can happen. Humans can more easily exchange this professional knowledge. If you look at an XBRL taxonomy, such as the US GAAP or IFRS taxonomies, you quickly realize how much information they really contain. That information will continue to grow as more people understand what they can do with XBRL and add even more domain knowledge to these XBRL taxonomies. For example, the XBRL taxonomy will grow to become an even more powerful ontology. (Chapter 17 explains the difference between a taxonomy and an ontology and why we believe that the taxonomies of today will look more like an ontology in the future.)
What makes this new communications medium even more powerful is that computers can help users of this information because software applications can also be made to understand this information. You can simply do more things with the information because the information is in XBRL.
Think about how topics changed the world. A topic can document information that one individual had in his head and transfer that knowledge to another individual. XBRL does the same thing. XBRL enables deep domain knowledge to be transferred to other humans and to computers, which further help humans make use of the information.
Fitting into the Extended Enterprise
How business intelligence is practiced has gone through an evolution, but what business intelligence is supposed to achieve has always been the same. Business intelligence is the ability of a business to understand the interrelationships between information and convert this understanding into competitive advantage and stakeholder value. Business intelligence has existed as long as there have been businesses because businesses are always looking for ways to obtain a competitive advantage.
In the earlier ages of business, getting information between continents or across continents could take months. In our modern age of computer information systems, we can exchange information from any point on Earth to any other point in a matter of seconds. Anyone can provide or consume information that can be in pretty much any format, including audio and video.
Business intelligence in the age of the computer has gone through an evolution. At first, reports were generated from isolated systems because computers were disconnected. Obtaining external information was difficult, and it was even more difficult to use the information even if it was collected because the format was generally not reusable without a lot of work and money, making it out of reach for most.
Eventually, systems evolved until separate systems gathered information into data warehouses or data marts, which made reusing the information easier but still costly. There was a trend toward getting all data into one homogeneous enterprise system. Generally, all this information still came from within an enterprise. But businesses still needed a lot of information from customers, suppliers, and other business partners to operate effectively and efficiently. More and more information was beyond the physical boundaries that an enterprise could make use of. Although the Web created the possibility of making use of this information efficiently, it also showed that because of the many different formats the information takes, reusing this information could be quite challenging.
As the connectivity of the Web became ubiquitous and inexpensive, businesses realized that they could use standards to minimize the problems of heterogeneous systems, making them operate more like a homogeneous
system. Besides, getting businesses to agree on one common homogenous system is something that will never be achieved and is, in many cases, an unrealistic approach to integrating systems.
The term extended enterprise represents the idea that an organization is made up of not just its employees, but also its agents, suppliers, customers, and other partners on which a business relies to conduct business. You knowing the inventory of a supplier in real time, for example, or a customer knowing what you physically have on hand in your inventory is the information that greases the economic engine of commerce. The understanding that we’re truly part of an extended enterprise is a realization that we’re all interconnected in a global network and that the network runs on information. As we discuss in Chapter 7, we are, after all, part of an information-supply chain. The cost of interconnecting the extended enterprise has never been lower.
Maximizing Economics of Information
The purpose of information is to serve decision-makers, allowing them to arrive at better decisions. What is the value of better decisions? What is the value of spending five minutes instead of two hours to reach a conclusion? What is the value of having information now rather than in two days? Clearly, this answer depends on the impact of the decision, but you get the idea.
Organizations generally have a significant asset in the form of knowledge and insight. Unfortunately, at the present time, the vast majority of organizations have this information scattered among disparate systems and sub-organizations within the larger organization, which makes the knowledge and insight challenging to discover. And discovering knowledge and insight are even more challenging if you consider the extended enterprise (see the previous section).
An information-supply chain helps reduce the friction within this process of exchanging and then using business information (see Chapter 7). It’s possible today to coalesce and harness knowledge of information to a versatile platform-agnostic format that you can leverage vertically and horizontally, across an organization and externally with business partners.
Walmart’s key competitive advantage is its global information-supply chain. Walmart manufactures no products (see Chapter 7). With the cost of establishing an information-supply chain so low, and the benefits of having one so high, you can easily see why XBRL is considered transformational. Industry dynamics will change — they’re changing now. How can you participate in these changing dynamics? Chapter 11 helps you see the different approaches to participating in the transformation XBRL has delivered. Chapter 12 shows you how to leverage XBRL’s power in a practical manner.
