Business Analytics & Intelligence
An Introduction and Considerations for Getting Started
Durham County White Paper
By Greg Marrow, IT Director [email protected]
919-560-7003
January 2018
Contents
Section 1 ...... 3 Executive Summary ...... 3
Section 2 ...... 3 What is Business Analytics (BA)? ...... 3 Benefits of Data-driven Decision Making with Business Analytics ...... 3 The Basic Pillars of Business Analytics ...... 4 The Four Basic Types of Analytics ...... 5 Big Data Analytics ...... 6 Examples of the use of Business Analytics ...... 6
Section 3 ...... 8 What is Business Intelligence (BI)? ...... 8 How can Business Intelligence Benefit My Organization ...... 9 The Difference Between Business Intelligence and Business Analytics ...... 9 The Stages of Business Intelligence ...... 9 How does Business Intelligence Work? ...... 10
Section 4 ...... 11 Getting Started with Business Intelligence ...... 11 Information Needs Assessing ...... 11 Data Considerations ...... 12 Business Strategy ...... 13
Section 5 ...... 14 Conclusions ...... 14
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Section 1 Section 2 Executive Summary What is Business Analytics? The concept of Business Intelligence (BI) has been around in various forms for more than a Business Analytics in its most basic form, is the century and a half. And we have used the study of data through statistical and operations terms Business Intelligence (BI) and Business analysis, the formation of predictive models, Analytics (BA) quite extensively here within the application of optimization techniques, and the County over the last 12-months. We have also communication of these results to customers, seen a few BI demonstrations and now have business partners, executives, and others. some departments that are piloting the Business analytics is about “anticipate and act” Microsoft PowerBI tool. The intent of this to drive Better Outcomes, Smarter Decisions, White Paper is to provide an executive level and Actionable Insights. Analytics is an “short and quick” overview of BI and BA to set umbrella term that encapsulates data a foundational understanding for those who collection, statistics, data mining, predictive may be new to this space and for those who modeling, and decision sciences. may be thinking about how to become more data-driven given the performance Business Analytics Basic Building Blocks – management work we’re doing with Managing Gartner’s Four Pillars for Results, utilizing BI and BA. The basic building blocks for BA must address This paper provides some basic definitions for data, people, process and technology, the terms BI and BA including a basic definition according to Gartner’s Jamie Popkin. These for Big Data. It gives examples of each along building blocks, referred to as the four pillars with explaining the difference. The paper of Business Analytics, helps to remind us of 4 describes different levels of BI/BA to help the key areas we must give consideration to when reader/organization determine where they are considering implementation of BA. in the continuum. It has been my observation that some business units are at the very Benefits of Data-Driven Decision Making with beginner stage and others are more advanced. Business Analytics We also introduce a BI/BA framework that has been used in the industry by one of the major Organizations use Business Analytics (BA) to consulting firms to help guide the discussion make data-driven decisions. The insight gained around BI/BA. by BA enables these organizations to automate and optimize their business processes. In fact, And finally, the paper concludes with a section data-driven organizations that utilize Business entitled, getting started with BI. The intent of Analytics achieve a competitive advantage this section is to provide some fundamental because they are able to use the insights to: guidance on considerations that must be given to people, processes, and technology including • Conduct data mining (explore data to data, when considering the utilization of BI. find new patterns and relationships) This is fundamental information that is Complete statistical analysis and provided to solely educate the reader on the • quantitative analysis to explain why fundamentals of Business Analytics and certain results occur Business Intelligence. This paper does not attempt to endorse any particular products. • Test previous decisions using different forms of data analysis
• Make use of predictive modeling and predictive analytics to forecast future results
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Business Analytics also provides support for to disparate data sources – regardless of organizations in the process of making their type and location. Being able to proactive tactical decisions, and BA makes it harness all the data available and serving possible for those organizations to automate it up to the business user is a critical base decision making in order to support real-time component to a solid strategy. responses. 2. Organization (People) -- as Business Analytics moves away from a centralized In summary, BA provides support for strategic model and towards a decentralized model planning, delivers tactical value, and creates via a more self-service design, the people competitive advantage. need to be trained and empowered to know how to use the data. The Basic Pillars of Business Analytics 3. Fact-based decision making (Process) Gartner, a major worldwide consulting firm, – the process pillar requires having the says BA must address data, people, process right information at the right time to make and technology. They call this the Four Pillars better, faster decisions. Because different of Business Analytics as show in the diagram roles make different decisions, it’s below. The intent behind the four pillars is important to leverage the same data to simply to help ask better questions – and get support a variety of processes. For better answers when developing business example, operational and executive users analytic applications. require dashboards; customers/citizens want statements, proposals and reports; A brief summary of each pillar is provided and departments need performance below: scorecards.
1. Information management foundation 4. Appropriate technology platform (Data) – the data pillar balances (Technology) – the technology pillar governance and access in the information- encompasses development and driven enterprise. It requires connecting
Figure 1: Gartner’s Four Pillars of Business Analytics
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deployment, with systems that break down volume; a manufacturer – silos of capability. The main point here is a rate of the products for organizations considering BA, to build a returned for a past month, flexible architecture that can be easily etc. These findings simply adapted to business needs. signal that something is wrong or right, without explaining why. For this reason, highly data-driven companies do not content themselves with descriptive analytics only, and prefer combining it with other types of data analytics.
2. Diagnostic – A look at past performance to determine what happened and why, and is characterized by techniques such as drill- down, data discovery, data mining and correlations. The result of the analysis is often an analytic dashboard. Organizations go for diagnostic analytics, as it gives a deep insight into a particular problem. Let’s look at some Figure 2: Analytics Value examples from different industries: a healthcare The Four Basic Types of Analytics provider compares patients’ response to a Gartner, also defines the four basic types of promotional campaign in analytics as illustrated in Figure 1. Figure 2 different regions; a retailer shows the more complex an analysis is (base drills the sales down to on the type of analytics), the more value it subcategories. And, in the brings an organization/business. healthcare industry, customer segmentation coupled with several filters The four basic types of business analytics can applied (like diagnoses and be defined as follows: prescribed medications) allowed measuring the risk 1. Descriptive – Descriptive analytics of hospitalization. answers the question of what happened. Descriptive analytics, the simplest form of analytics, means looking 3. Predictive – Predictive analytics means at historic data, ranging from 1 minute ago using all that data to make a prediction to years ago. It can be compared as about where to go; it is the navigation that looking in the rear mirror while driving. tells you how to drive and when you will Ninety percent of organizations use arrive. It uses the findings of descriptive descriptive analytics and often when and diagnostic analytics to detect people think Business Intelligence, this is tendencies, clusters and exceptions, and to what they’re referring too`. For instance, predict future trends, which makes it a a healthcare provider will learn how many valuable tool for forecasting. Despite patients were hospitalized last month; a numerous advantages that predictive retailer – the average weekly sales analytics brings, it is essential to
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understand that forecasting is just an difficult to analyze); and variety (the range estimate, the accuracy of which highly and type of data sources are too great to depends on data quality and stability of the assimilate). situation, so it requires a careful treatment and continuous optimization. Thanks to predictive analytics and the proactive Structured data is comprised of clearly approach it enables, a telecom company, defined data types whose pattern makes them for instance, can identify the subscribers easily searchable; while unstructured data – who are most likely to reduce their spend, “everything else” – is comprised of data that is and trigger targeted marketing activities to usually not as easily searchable, including remediate; a management team can weigh formats like audio, video, and social media the risks of investing in their organization’s postings. expansion based on cash flow analysis and forecasting. And, some companies have What’s important to keep in mind about Big gone one step further to use predictive Data is that the amount of data is not as analytics for the entire sales process, important to an organization as the analytics analyzing lead source, number of that accompany it. When companies analyze communications, types of communications, Big Data, they are using Business Analytics to social media, documents, CRM data, etc. get the insights required for making better business decisions and strategic moves. Here 4. Prescriptive – The purpose of prescriptive are a couple of very basic Big Data analytics analytics is to literally prescribe what examples: action to take to eliminate a future problem or take full advantage of a • Fast food and video. There is one promising trend. This is the most valuable company now training cameras on drive- kind of analysis and usually results in rules through lanes to determine what to display and recommendations for next steps. on its digital menu board. When the lines Prescriptive analytics is the self-driving car, are longer, the menu features products that knows exactly what the best route is that can be served up quickly; when the based on infinite data points and lines are shorter, the menu features calculations. Not surprisingly, Google’s higher-margin items that take longer to self-driving car makes extensive use of prepare. prescriptive analytics. And, in the health • Macy's Inc. and real-time pricing. The care industry, you can better manage the retailer adjusts pricing in near-real time for patient population by using prescriptive analytics to measure the number of 73 million (!) items, based on demand and patients who are clinically obese, then add inventory, using technology from SAS filters for factors like diabetes and LDL Institute. cholesterol levels to determine where to focus treatment. The same prescriptive Examples of the Use of Business Analytics model can be applied to almost any As stated above, many organizations are industry target group or problem. utilizing analytics to improve business Prescriptive analytics gives you a laser-like efficiency. Every day organizations collect data focus to answer specific questions. about their customers and industries, simply as an artifact of the act of conducting business. However, world-class organizations tend to Big Data AnalyticsBig Data has taken the leverage analytics 5 times more than other world by storm. The intent of this white paper (MIT Research). is not to discuss Big Data in detail but to give a basic definition for it since this term is also Analytics is growing exponentially in thrown around a lot. SAS (company located in competitive segments like consumer Cary, NC) describes Big Data as “a term that describes large volumes of data – both marketing. For example, NetFlix mines its structured and unstructured – that inundates a video rental history database to recommend business on a day-to-day basis.” Big data is rentals to individual customers. American characterized by three primary factors: volume Express can suggest products to its cardholders based on analysis of their monthly (too much data to handle easily); velocity (the expenditures. speed of data flowing in and out makes it
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A widely quoted example of predictive analytics The framework, without going into a lot of insight is the Diapers and Beer sales co- detail, defines the people, processes and relation. A grocery chain uses Predictive technologies that need to be integrated and Analysis to analyze local buying patterns. They aligned to take a more strategic approach to discovered that when men bought diapers on business intelligence, analytics and Thursdays and Saturdays, they also tended to performance management (PM) initiatives – buy beer. Further analysis showed that these particularly when considering an enterprise shoppers typically did their weekly grocery approach. Gartner recommends that shopping on Saturdays. On Thursdays, organizations should use the framework to however, they only bought a few items. The develop a strategy and an implementation retailer concluded that they purchased the plan, and to surface key decisions, integration beer to have it available for the upcoming points, gaps, overlaps and biases that business weekend. The grocery chain could use this leaders may not have otherwise prepared for. newly discovered information in various ways Gartner also points out, that a portfolio of to increase revenue. For example, they could information management, analytic and move the beer display closer to the diaper decision-making capabilities will be needed to display. And, they could make sure beer and meet the diverse requirements of a large diapers were sold at full price on Thursdays. organization.
The Business Analytics Framework Again, the intent of the framework is simply to illustrate graphically all of the components that must be considered including people, As we think about the utilization of Business processes, and technology when considering Analytics, we must give consideration to Business Analytics. And, there is no single or people, processes, and technology – especially right instantiation of the framework; different if we’re considering BI for the enterprise. configurations can be supported by the Gartner, the consulting firm, defined a framework based on business objectives and Business Analytics framework several years constraints. ago in order to provide a blueprint for success, particularly for small and midsize organizations getting started with BA. A key benefit of the framework is “to surface key decisions, integration points, gaps, overlaps and biases that business leaders may not have otherwise prepared for” when getting started with BA.
Figure 3: Gartner Framework for Business Analytics
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people, processes and applications/tools to organize information, enable access to it and analyze it to improve decisions and manage Section 3 performance.
What is Business With Business Intelligence, we can discover Intelligence? actionable trends that have been hiding amongst millions of data rows and business processes.
Business Intelligence: • focus is on retrieval and delivery of
data
• monitoring and identifying exceptions
• limited variability, ambiguity, uncertainty • reporting, dashboards, scorecards…
Business intelligence (BI) software allows organizations to tap into their many databases In its most basic form, Business Intelligence and deliver easy-to-comprehend insight to (BI) is the process of turning data into management, employees, and other key “actionable” results. BI is about understanding stakeholders. BI software -- query, reporting, the facts – and the relationship between the analysis, scorecards and dashboards — is facts – in a way that guides decision-making already being used by thousands of companies and action. Data is everywhere but unless it is to find new revenue opportunities, reduce motivating enough to take action, it is in costs, reallocate resources, and essence, only informational and useless. improve operational efficiency. The most Gartner, the global IT consulting firm, defines widely used BI tool in the world is Microsoft “BI” as an umbrella term that spans the Excel.
Figure 4: Benefits of Business Intelligence
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And finally, BI allows us to do the different What’s more, the results are not always forms of Business Analytics discussed accurate or insightful. While Microsoft Excel previously. has many excellent uses, it’s like using a hammer when you need a jack hammer. How can Business Intelligence Benefit My For bigger tasks, like taking an Organization? organization to the next level, you may need bigger, better, faster, and more BI offers tools to manage the impossibly large efficient tools. amount of data available to an organization. This includes data previously isolated in silos across the enterprise. In addition, BI tools can The Differences between Business now allow integration with data from and other Intelligence and Business Analytics sources outside the organization boundary. When properly implemented and understood as Business Intelligence (BI) and Business an organizational philosophy, BI enforces data Analytics (BA) are similar, though they are not standardization and integration, offering a view exactly the same. Business Intelligence of the organization that is panoramic and that involves the process of collecting data from all was previously unobtainable. With such a view, sources and preparing it for Business Analytics. new insights into operations and performance Business Intelligence is more of a first step for can emerge and that may result in better organizations to take when they need the decisions and eliminate problems such as: ability to make data-driven decisions.
• You can’t make the best decisions to Business Analytics, on the other hand, is the drive higher performance because you analysis of the answers provided by Business don't understand the Why behind Intelligence. While Business Intelligence current results. answers what happened, Business Analytics • Meetings bog down in multiple versions answers why it happened and whether it will and interpretations of the truth. happen again. Business Intelligence includes • Current reports are too complex for reporting, automated monitoring and alerting, action; have too much data and not dashboards, scorecards, and ad hoc query; enough actionable information; tell Business Analytics, in contrast, includes inconsistent stories about your statistical and quantitative analysis, data organization or business unit. mining, predictive modeling, and multivariate Analyzing performance on key business testing. Today, when you hear the term drivers is near impossible. Business Intelligence, it normally means all of the above capabilities. In short, BI is about information analysis. A database pulls together information from the different parts of your business, then The Stages of Business Intelligence applications convert that raw data into reports, charts, and other analytical tools to provide We all use Business Intelligence concepts in insight. The benefits of this insight include: one way or another, an everyday example being a financial report such as a bank • It’s much easier to make informed statement. The level of Business Intelligence decisions. maturity depends on organizational goals for • It improves the efficiency of turning data into actionable results. In doing business operations. the research for this whitepaper, I came across • It can enhance the quality of the Affirma Business Intelligence maturity customer service. curve. Affirma is another BI consulting company. I like the maturity curve, because These are not small achievements. They for some organizations as an example, are the key factors to business success and application specific reports may be sufficient. prosperity. Attempts to analyze data However, what the curve illustrates, is that as without BI can be clumsy. For instance, an organization matures their Business information is often tabulated on Microsoft Intelligence practices, the more benefits and Excel spreadsheets. It is time-consuming investment return will occur. collecting the data and tedious putting it together in a way that’s easy to grasp.
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The five stages of the Affirma Business prepared data, but there is often an Intelligence Maturity Curve are: additional need for historical reporting, ad- hoc analysis, and scheduled automated 1. Application-Specific Reporting – most refreshing of data. Adding some additional business software applications have built-in technologies provides the ability to analyze reports to provide statuses and/or insights multiple perspectives or slices of data at into actionable data. Example, the County’s one time. Human Resources (HR) Application has 5. Fully Integrated Business Intelligence built into it a number of application specific System and Process – This Business reports including our SAP system Intelligence solution provides insights into 2. Data Analysis Tool – application-specific your organization’s data, but is essential reporting is not sufficient to answer all when there is a need for self-service business inquiries and additional analysis is reporting. Employees want to analyze required, often times through exporting information on their own with minimal IT data into a tool such as Microsoft Excel. As support, and advanced methods for storing mentioned earlier, the most widely used BI changes to a centralized data repository tool is Microsoft Excel. – sometimes referred to as a data 3. Visual Data Analytics Software – data warehouse. analysis is completed, but the information As an organization or department, you may needs to be analyzed beyond the use the graphic in Figure 5 to assess where capabilities of the data analysis tool. A you are on the maturity curve today and Business Intelligence solution such as what are your business goals. Microsoft Power BI or SAS can help prepare intelligence visualizations and How does Business Intelligence Work? dashboards. Business intelligence (BI) provides a spectrum 4. Advanced Technology Implementation of broad range analytical applications, – This Business Intelligence solution including collaborative BI, mobile BI, open creates stunning data visualizations using source BI, SaaS (software as a service) BI,
Figure 5: The Five Stages of the Business Intelligence Maturity Curve
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operational BI and real-time BI. The enabling better insight and action. This technology is not just about gathering uniform, transformed, consistent data requires intelligence but about making sense of data in data governance. Data governance will be a way that can be quickly grasped. discussed in more detail in a future white paper. This is accomplished through visualization applications for creating infographics and designing charts (see Figure 6). BI also offers dashboards, as well as performance scorecards. In essence, key performance indicators and business metrics are much Section 4 easier to understand when displayed as visualized data. Getting Started with
The diagram below attempts to summarize in a Business Intelligence very simple pictorial how BI works starting with the different data sources on the left (data Business Intelligence (BI) is not a single piece moves from left to right). Data from disparate of software or even a suite of software to sources is extracted, transformed and loaded crunch data (or big data sets). Instead, it is an (data preparation) into different technologies umbrella term that includes best business (data infrastructure) where it is at the beck practices, software, infrastructure, and any and call of users via a friendly intermediary BI other tools to optimize decision making and software layer (right most block) that provides enhance performance. Now that you are the actionable intelligence needed (via reports, familiar with BA and BI, the stages of BI, and dashboards, etc.) to make data-driven the different types of business analytics, you decisions (example the Budget Dashboards may be asking the question, how does my that have been produced by the Budget Office organization leverage BA and BI to become using a tool called PowerBI). The goal being more data-driven in order to drive effective where users across the enterprise access the decision making. same store of uniform, transformed data, The intent of this section is to provide some very basic information to help guide the thinking around the use of BA and BI, starting with an assessment of your information needs, some basic data considerations to keep in mind, and concluding with some important thoughts around business strategy.
Information Needs Assessment
Any of the following signs could indicate that information needs and opportunities in your organization are outstripping the solutions currently at your disposal:
1. Your organization has lots of data, but little information. Information is data that has been converted into useful insights, forecasts, and recommendations. 2. You are not getting what you need from the Application Specific reporting capabilities from the systems being used within your organization. 3. You have hit a spreadsheet wall. Many organizations start with Excel or Figure 6: Components of Business Intelligence another spreadsheet application to hold and analyze their data. However, this
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approach can rapidly become 1. Data structure. Data from different unmanageable, as larger datasets and files sources relating to the same subject may start to choke the spreadsheet software. be structured differently. In the example Attempts to break datasets down into above of the HR and Finance departments smaller chunks may simply push holding employee information, HR might organizations into departmental data silos use several spreadsheets for employee that prevent good business insights from personal details, job responsibilities, and being generated or shared-across the qualifications, where Finance only uses one enterprise. to record insurance, benefits, and similar 4. Joining data from different sources is data. In the different spreadsheets, a headache. Even simple differences in employees might be listed by grade, or by the way two departments fill out department, in overall alphabetical order, spreadsheets with similar, but not identical with initials only, or with both given and data (for example, HR and Finance each family names, and so on. This is a simple with their own subsets and formats of example. Other differences in data employee information) can make it hard to structures between business groups can be combine the spreadsheets for analysis. significantly more complex. 5. Your data visualization lacks insight. To tell a useful story, data visualization 2. Data size. Data may come in gigabytes, must use metrics and indicators that are terabytes, or petabytes. However, overall directly relevant to a business. Simply volume is not the only consideration. Data totaling rows or columns and making a bar may also be organized into thousands or chart or a pie chart may not be enough to millions of rows, columns, and other tell you if your organization or the dimensions, needing correspondingly enterprise is doing well or at risk, or may powerful solutions to analyze and compare, lack the intuitive impact of key dimension by dimension. performance indicators that a good business intelligence solution can produce. 3. Data sources. The more data sources there are (see Figure 6), the higher the Data Considerations chance of differences in internal data structures and formats, or of data that has If you’re strictly looking at utilizing a BI no specific format. Data from the different solution just for your departmental data, sources must be brought together and understanding data complexity (data structure, harmonized in one location to ensure data size, data type, data sources, etc.) is very comparisons and analyses are “like to like”. important. Example: let’s say you’re only looking at Risk Data and you would like to get The above are just a few data considerations some visualizations, dashboards, and more that must be taken into account. Others advance reporting capabilities, then the include data type, query language, data detail, considerations here may not be as complex as and data growth rate. This should also include if you were looking to combine data from creating a plan for data storage. Are the data multiple sources. sources going to remain disparate? And lastly, clean data in, clean analytics out. It’s that If however, the organization is looking at simple. Cleaning your data may not be quite as building an enterprise BI solution, a fully simple. But it will help ensure the success of integrated BI Solution and Process (see Figure your BI. 1), which is the long-term goal of Durham County Government, then many of the criteria Summarizing, the need for utilizing a business identified above (data structure, data size, …) intelligence solution to handle complex data must be considered in mapping out an may become obvious in simple ways. A approach to BI. current lack of actionable insights and difficulties in combining multiple spreadsheets Understanding and evaluating the complexity are just some examples. And understanding of the data is a key step in mapping out an and evaluating the complexity of your data approach to BI. Below are some examples to against the right criteria will help to determine explain what we mean by evaluating the business requirements, capabilities, and complexity of the data. resources required to get started with Business Intelligence.
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Business Strategy 5. Go into the process with eyes wide open. When you have the right BI solution, it is Clearly defined business strategies and easy to identify trends, pitfalls and objectives are critical to the success of any BI opportunities early on. But implementing the and analytics initiative. Below are 5 key points right solution isn’t always easy. Actually, it (and there are many others) to consider and usually isn’t. We are going to be honest keep in mind: here, even the best BI software needs some initial heavy lifting to maximize its potential. 1. Organizations should know or have some If you go in with the right mindset you will idea of what business insights they want, be prepared to address issues like and which ones are most important. complicated data problems, change 2. It is highly recommended that management resistance, waning organizations focus on the business sponsorship, and user adoption challenges. problem first, then on data. Identify a Reminding stakeholders, and yourself, of the clear business problem first, what metrics you want to analyze, and then where to pain points that necessitated BI will get the data. encourage the process forward. It will be 3. Ensure key stakeholders are involved from worth it. within and across the organization (if building an enterprise BI solution). By Again, we’ve provided some very basic involving a range stakeholders you can considerations that must be taken into account ensure you cover the three broad classes when considering BI and analytics. These are of business intelligence users: strategic, important to ensure an organization does not tactical and operational. These different end up with data silos. users’ types will need customized solutions. Understanding who will use the The graphic below, Figure 7 attempts to data and for what purposes can show the summarize from left to right, with a bit more type of information needed and its detail, our attempt here to identify some key frequency, and help guide your decision considerations when considering BI and making. analytics. 4. BI is not just a technology solution. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. But every stakeholder and their respective business areas should also be involved throughout the process.
Figure 7: Analytics Delivery Services
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Section 5 Conclusions The intent of writing this white-paper was to provide a short 3-to-5 page introductory-level overview of Business Analytics (BA) and Business Intelligence (BI). As you can see, the paper turned out much longer than planned however I hope the paper provided an understanding of the basic fundamentals of BA and BI, and some basic considerations for thought when thinking about BI readiness, whether within your organization or across the enterprise.
If you have read this whitepaper and would like to sit down with someone to talk further about how you get started with Business Intelligence, please do not hesitate to reach out to me or submit an IS&T project request form through the IS&T service desk. Our goal is to empower individuals and departments with the tools necessary to conduct their own BI, referred to in the industry today as self- service BI. Self-service analytics allows organizations to bring business intelligence capabilities to users at all levels. Even with Self-Service BI however, it requires the right guidance as indicated in this paper to build-out a successful BI approach.
And finally, I want to thank all of those who contributed to this whitepaper including our Budget Department who is leading with turning data into information through the work they are doing with business intelligence. They are also a good resource here within the County to talk with regarding their approach to BI.
Thank you for taking the time to read this paper.
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