Business Intelligence for Law Firms. Zena Applebaum

Transcription

1 Zena Applebaum Published by In association with

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3 Chapter 1: Setting the stage for intelligence Every decade and with every new management book on the best sellers list, it seems there are new business terms, ideas and trends penetrating the market. From blue ocean strategies 1 to tipping points 2 to creative classes 3, it seems there is always some new technique or challenge facing businesses that they did not even know was an issue. Most recently, the concept of intelligence as a business discipline has been added to the roster of administrative departments in professional services firms as well as in consumer goods and other industries, whether it is referred to as business intelligence (BI), competitive intelligence (CI) or market intelligence (MI). Intelligence in any form has its roots in military operations, where armies would use intelligence they had gathered from reconnaissance missions to inform their battle strategy or plan their next tactical move. Small units of people would gather, almost secretly, to compare notes, share experiences and commit little to paper. Intelligence in those terms is often thought of as synonymous with spying or corporate espionage, and is therefore seen as an unethical and shady practice. Presumably, though, as intelligence has become a buzzword of modern business and entire departments, and professional associations have been set up to support the practice, intelligence is very different to its original military description. Surely, this is an accepted and encouraged strategic business discipline. Moreover, if there are three different designations for the types of intelligence being collected and analyzed in companies, there must be a difference between the three disciplines. There are several differences, but before this is discussed it is worth taking a step back and looking at why it is that intelligence has become important at this moment in time. Information overload It is tempting here to make a popular music reference to a 1990 s song called Information overload by the band Living Colour, as the current era is an era of information overload. Once upon a time, as with military intelligence, a person could gain the upper hand over his or her opponent by knowing more, or possibly even by having more information or access to information. Today however, with the internet, smart phones, social media and apps for everything imaginable, information is everywhere and accessible all the time to almost anyone. If there was a term more overarching than ubiquitous, it could describe the amount and frequency with which people interact with information or data inputs of some kind or another on a daily, or even hourly basis. More to the point, information in mass quantities is accessible to almost everyone, particularly in the Western world, whenever it is desired. There are 24-hour internet cafes, coffee shops and fast food chains with free Wi-Fi, and even air travel is not immune from the need for constant 3

4 Chapter 1 connection to information. People have more information literally at their fingertips than many local libraries once had in thousands of square feet of books. Having information or data is no longer a competitive advantage. The glut of messaging and information available to people could actually have the reverse effect and prove to be a disadvantage. Often referred to as information democracy or dystopia, the glut of information and what it all means can overwhelm a business. If information as a raw input is a disadvantage, then the ability to turn information into intelligence is an advantage. Going a step further, the ability to take that intelligence and turn it into action is the ultimate business strategy. Modern day competitive advantage then comes from the ability to tag, categorize, store, retrieve, analyze and most obviously use the right data or information at the right time. Call it BI, CI or MI, the concept of capturing useful data, taking it apart and repurposing it for some competitive or commercial advantage is the new Holy Grail of the business world. What is in a name? What, then, is the difference between the various types of intelligence? Is it how the information is collected, stored or used? Are different information inputs, research and analysis methodologies required? Or are all three intelligences essentially the same thing with different names? Business intelligence Traditional business literature defines BI as the ability of an organization to take all its capabilities and convert them into knowledge, ultimately getting the right information to the right people, at the right time via the right channel. 4 More often than not, BI refers in some ways to data warehousing and data mining, and is often software or technology driven. Frequently, the intended purpose of a robust BI program is to help a company determine what it knows, or put differently to increase efficiencies based on the data or information that is flowing throughout the organization. The data, when assessed, should in some way lend themselves to process improvements, financial savings, risk mitigation, determination of excess expenditure, or point to particular areas of an organization that are overburdened. The outputs of traditional BI reporting are tables and charts with some supporting narrative that can visually represent large numbers of data by breaking down those metrics into manageable chunks. BI is highly data driven and generally speaking requires a significant amount of data from which to make assumptions and draw conclusions. Loyalty programs at retail outlets, service providers and chain restaurants are the types of places that passively collect this type of data with surveys, credit card swipes and metadata from online transactions being recorded. The data that supports BI is often collected, stored and mined at a specific moment in time as the impetus for a pricing decision, a new service offering, a process improvement project or something similar that requires looking at a task or series of tasks over a period of time. The data is rarely archived, but continues to be included in future data sets as needed. The larger the data set, the more accurate or complete the intelligence can be. For example, large hotel chains will mine the data collected at check-in to determine the demographic data of their guests by age, home address (the place they are visiting the hotel from), number of people in the party, activities booked, special accommodations (such as technology needs, crib requirements and 4

5 pet-friendly floors), room service selections and the like. Once patterns are ascertained, the hotel can create marketing campaigns targeted to the demographic age- or geography-wise that are most likely to visit. The hotel can also start to offer new services that are in line with the BI collected. BI, with its strong reliance on technology, often uses dashboards and scorecards for reporting. A typical dashboard or scorecard would present with several easy-to-read pie charts, line graphs and other visually appealing representations of the data. Since the data is mostly quantitative in nature, the visuals make it easy to understand the story the numbers are trying to tell. A typical dashboard may have one or more tabs with different data representations. Figure 1 gives an example of the type of data that might be seen represented on a dashboard. Since BI is heavily numbers-oriented, the analytical tools used tend to be very straightforward statistical analyses. Competitive intelligence CI, as defined by strategic and competitive intelligence professionals, is a systematic and ethical program for gathering, analyzing, and managing external information that can affect you. The you here refers to any business, association, partnership or firm. CI is all about understanding the external information that can change or alter a business. For many, the term CI conjures up images of spies rooting through the rubbish bins of competitors or stealing information about what a competitor is doing. There are urban legends in CI of hotel conference rooms being monitored, searched and cleaned by competitors following annual sales meetings and the like. This, of course, is not the case. CI is actually a highly ethical practice that involves gathering information through publicly-available documents, specifically tailored primary research, subscription databases or other morally acceptable Revenue trend Deals won vs. Lost trend Revenue Quota CAN Millions Won Lost Q Q Q Q Q Q Q Q Q Q1 Information technology 8% Customer service 5% Employees per department Other 5% Marketing 14% Sales 27% Accounting 41% CAN Millions Monthly revenue and expenses Revenue Expenses Q Q Q Q Q1 Figure 1: Typical business intelligence reporting that may be represented on a dashboard 5

6 Chapter 1 means and then analyzing it with a set of analytical tools or methodologies. The analytical tools used to carry out CI analysis depend on what a company hopes to achieve. Often CI analysis will make use of well-known analysis frameworks such as SWOT (which stands for strengths, weaknesses, opportunities, threats), four corners, historiographic or timeline analysis or Porter s five forces analysis. Where CI is concerned, the analysis framework used can have as much of an impact on the information as the information itself. For example, a timeline analysis can help make predictions about a product or a product launch with time-specific implications; whereas a five forces analysis might provide a better framework for determining the effects of a new market entrant. CI is primarily concerned with anything that will make an organization more competitive and able to avoid surprises from its competition, suppliers and customers or service users. While many theorists in the area focus on competitors in a given space, the most successful CI functions at wellknown organizations, such as Dunkin Brands and Motorola, are focused not only on competitors and new market entrants but also on market trends and the general competitive market place. Ultimately, CI is about getting in front of the product or service to provide clients and consumers with a reason to pick and stay with the offering despite the choice offered in a competitive market. CI is forward looking and requires a vigorous collection, analysis, dissemination and repeat cycle. To achieve the best results, CI often requires the triangulation of source data, both primary and secondary, as well as the application of multiple analysis frameworks. Since CI is heavily dependent on anecdotal information, as well as primary and secondary research, the reporting mechanisms tend to be less technologically and visually driven and are based more on written reports and narrative summaries of issues. Reporting, however, should still be concise and to the point with a clear call to action. Market intelligence MI, the third type of intelligence gaining momentum in the market place, derives its genus from the market; in other words MI is the information relevant to a company s markets, gathered and analyzed specifically for the purpose of accurate and confident decision-making in determining market opportunity, market penetration strategy and market development metrics. MI is therefore based on market research and is very focused on market dynamics. This discipline, unlike BI or CI, is less concerned with long lead time, huge data sets or a triangulated approach to analysis. MI is much more focused, often leading to a specific marketing campaign, product development or other project-specific opportunity. Once the proverbial moment has passed since a moment can refer to weeks or even months the data supporting MI is quickly out-dated and new data comes along to take its place. MI data can be collected retroactively and collection is likely to fall into the domain of market research departments. MI, like BI, will include internal customer and client data, but will also take its inputs from macroeconomic or external market data. MI reporting tends to be a combination of BI charts and graphs, and CI narratives. Since MI is often very targeted and project-specific, the reports tend to reflect this and will mirror the needs of the particular assignment. Intelligence in any form The intelligence types are decidedly different. The purpose of each is unique and as 6

7 a result the way in which the supporting information/data/research is collected is different. At their root, however, there are some similarities. Intelligence is always about forecasting in some way. Information can tell you what is happening in the present tense. All a person has to do is pick up today s newspaper or read it online to know what is happening in his or her city or the world today. Intelligence however, whether BI, MI or CI, is about forecasting what will be based on numbers, anecdotal evidence or market trends. Intelligence is about predicting the future or making necessary changes in the present to accept the future in an effort to not be blind-sided by it. All three categories of intelligence share this one underlying trait. Table 1 illustrates some of the differences and similarities between the three different types of intelligence. The three types of intelligence can (and should) inform one another, borrow data and analysis from each other and work together to solve business issues. That said, each of the three is unique and require different skill sets, collection methods, time lines and approaches in order to be useful for the businesses it supports. Back up and security Another similarity between all three intelligence disciplines is the need for each of the data sets to be backed up and secured across the network or networks in which the intelligence practitioner is working. While it may seem obvious that any piece of work and data set should always be backed up, it is particularly important when dealing with intelligence, some of which cannot easily be replicated. The data that flow through an organization are vulnerable to hacking, power outages (whether scheduled or otherwise), maintenance checks, viruses, etc. It is important to remember that whatever system of data collection and analysis is used, a secure back-up system is always in place. Back up can happen on the premises, offsite or in the cloud, but should be a prerequisite to any intelligence program. Security is an in-depth topic that requires discussion in terms of how much or little security is required and at what level intelligence data should be protected. Chapter 9 of this report will explore some of these concepts in greater detail. Intelligence in law firms Knowing the difference between BI, CI and MI and some of their traditional uses begs the question: can these disciplines be successful in law firms? Is there even a role for these kinds of analysis or do law firms operate in a different business environment where they are not applicable? The answer, of course, is that yes, as a business and Type of intelligence Business Competitive Market Time Purpose Focus Collection Analysis Reporting Long data cycle Forwardlooking Projectspecific Increased efficiencies Avoid surprises Market capture Internal data Passive Software driven Graphic External data Active Manually Narrative driven Internal and Active Combination Combination external Table 1: A comparison of the differences between the three types of intelligence 7

8 Chapter 1 law firms are businesses BI, CI and MI should play a role in the development, support and execution of strategy. Specifically, as will be seen, daily tactical operations, client service, marketing and strategy can be enhanced through the use of the intelligences. Organizations often blur the lines between the three disciplines, practicing a hybrid approach to all three. Law firms, as a result of their reporting and billing structures, are the perfect storm from a hybrid approach. For example, sometimes a practitioner can start with a CI title, and quickly drop the C or competitive from his/her title when it is realized that the function is a combination of all three intelligence disciplines as a result of the unique informational needs and data capabilities of law firms. In Chapter 2 on law firms and their distinctive challenges, how and why this blurring of intelligence functions only gets intensified will be discussed. Rest assured though, all three intelligences are being actively pursued in the legal industry. As the industry increasingly moves toward perceiving itself as a business, service providers are recognizing the need to provide the legal industry with various intelligence products and services. These products include data collection software, data mining software, content creation software, company databases, client profiling software, news aggregators, public and private company information databases, disclosure document retrieval systems, cataloguing and meta tagging programs, portals, dashboards, and all manner of data analysis software. There are service providers who can work with firms to analyze their precedents, create model documents for increased efficiency, which is fundamentally a form of BI, facilitate primary research for CI, or moderate focus groups for MI. There are companies offering custom portals and dashboards to bring all of the intelligence together on one screen or that can segment different data types in different ways. There is almost no end to the quantity and quality of services and products available to firms in the area of intelligence. While one firm may have success with one suite of products and services, another firm may find a totally different set of vendors meet their needs. Whatever the criteria and whatever the strategy a firm is looking to support, the one thing that is clear is that the intelligence functions within businesses, including law firms, is growing. This represents a huge shift in the way business is done and perceived in the law firm, and this shift is a positive one for firms and clients alike. Business intelligence at the heart of knowing what one knows Since there is too much information in the world in general, this report focuses on the concept of BI in law firms. It looks at the myriad of internal data that is available in law firms. It considers what firms are doing or should/could be doing to capture and use this data to their competitive advantage in order to increase profitability, reduce overheads and increase efficiencies in drafting and document storage. This report will show how this internal data, when assembled together and analyzed, can help firms determine what they know to increase efficiencies and be better firms, client partners and businesses. In the next chapter, we will start to sort of out the difference for law firms and discuss why now, more than ever, intelligence in all its forms will be essential to the continued growth and success of the industry. 8

9 References 1. Chan Kim, W., Mauborgne, R., Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant, Harvard Business School Press, Boston, Massachusetts, Gladwell, M. The Tipping Point: How Little Things can make a Big Difference, Little Brown, Boston, Massachusetts, Florida, R.L., The Rise of the Creative Class: And how it s Transforming Work, Leisure, Community and Everyday Life, Basic Books, New York, Rud, O., Business Intelligence Success Factors: Tools for Aligning Your Business in the Global Economy, Wiley & Sons, Hoboken,