Business AnalyticsDeveloping an Evidence-Based

Approach to Improving Business Performance

Turning Data into Knowledge

Table of Contents1. Evidence-Based Decisions2. Gallo Winery3. What is Business Analytics?4. Data Mining5. Classification6. Clustering7. Profiling8. Co-Occurrences and Market Baskets9. Data Engineering: Relational

Database Technology10. Database Querying: SQL11. Big Data12. Descriptive Statistics13. Data Variability

14. Sampling15. Hypothesis Testing16. A/B Testing17. Data Visualization: Scatter Plots18. Data Visualization: Pie Charts19. Data Visualization: Histograms20. Data Visualization: Bar Charts21. Linear Regression22. Multiple regression23. Pivot Tables24. Pivot table Template25. Building the Pivot table26. Advanced Features: Pivot Tables27. Summary

PREFACE

Evidence-Based Approach to Management Decisions

Business Analytics, a relatively new field, is basically a collection of quantitative tools emphasizing an evidence-based approach to business decisions. It is interdisciplinary in that it brings together a wide range of topics from artificial intelligence, machine learning, database technology, statistics to data visualization.

It’s purpose is quite straight-forward; to help business professionals make sense of the increasing volumes of data now accessible to them. The assumption is that by making better sense of data, organizations can sustain a competitive position in an increasing competitive world of commerce.

Emphasis on ManagementBut how can mangers become knowledgeable in these disciplines? Each one is demanding by itself and takes considerable time to master. More importantly, knowledge at this level is usually beyond the needs of most business professionals.

The dilemma, however, is that they still need to understand what Business Analytics can do for their organizations. They need to understand how it can help them make the kinds of decisions that contribute to the firm’s ability to prosper in competitive markets. And they need to know where and when it can be used!

This course has been developed to address this dilemma.

What does a Business Person Need to Know?

Developing a course that brings together such a diverse collection of disciplines - each with its own theoretical framework and vocabulary - can quickly devolve into one that is lengthy, overwhelming, abstract and theoretical. This was not my intent. Instead, it was to develop one that provides an intuitive understanding of these disciplines, focus on applications and capture the essence of what a business person needs to know to recognize opportunities for their use.

My assumption is that once an opportunity is recognized a proper professional can be called in, if necessary. But it does not work the other way around. It does not work when a person skilled in these disciplines is brought into an organization and asked to find situations where they can be applied. Successful use of business analytics begins with the business person not with the statistician or data base professional. No one knows better than the business person where the real payoffs can be found.

General Concepts are Often Enough

Here is the surprising part. My experience has taught me that understanding the general concepts is often enough, especially for business professionals.

Let me explain with an example. One concept you will learn in this book is called hypothesis testing, a topic commonly associated with the discipline of statistics. To use this tool it is necessary to follow a procedure that involves three steps: data collection, data analysis and choice. Perhaps the most productive application of this tool is A/B testing were two alternative courses of action are identified, an experiment conducted, data collected and a choice made as to which of these alternatives should be chosen.

General Concept is Often EnoughConsider a website design project. A very basic challenge is to determine how it should be designed to attract the most attention. Here is where the concept of hypothesis testing can prove useful. It would encourage the designers to build two or more sites, identify the criteria against which the sites would be compared ( such as the number of hits, length of time on the site, and conversion to purchase), make the sites available to different market segments, collect the data for each of these criteria and then compare them using proper statistical methodology to determine which site has been more effective.

Hypothesis testing then suggests that alternatives are chosen, data collected and results compared. It is one of the tools that promotes and encourages evidence-based decision making.

Intuition, Experience and JudgmentThe value for many business professionals is not necessarily understanding the theory behind hypothesis testing, but understanding the general concepts and approach suggested by this statistical tool: create an experiment in which two or more ideas can be tested, collect the data and compare the data. So hypothesis testing is really a framework which helps to underscore the limitations of experience and judgment when comparisons must be made.

Real World ApplicationsBut learning the general concepts associated with these disciplines is not enough. It is also necessary to understand how, where and when they can be applied. Case studies often accomplish this goal and connect the gap between concepts and real-world application.

The use of short cases to illustrate concepts has always been important to me as a teacher and author. It is an approach that I have relied upon to illustrate how these concepts can be applied to the real world of business. This interest started when I worked full-time for General Electric, Boeing and Hewlett Packard. But it continued over my career as a Professor at the University of New Hampshire and as a consultant to wide range of organizations across the world. While concepts, and the theory behind them, have always held a fascination for me, I have constantly asked, how can they be applied? It is a curiosity that pervades this course.

GALLO WINERYChapter 2

IntroductionIn this chapter you will have the opportunity to explore how one company has created an evidence-based management culture, one that has certainly not neglected more traditional approaches to data collection and decision making but one that has also embraced a variety of contemporary data mining and statistical tools to further improve its competitive position.

Gallo WineryUnder great public pressure, prohibition was repealed in 1933 and within a short time 800 companies were competing to sell wine into what had become a very competitive market.

One of those companies was headed by two brothers, Ernest and Julio Gallo who had grown and sold grapes from their vineyards. With the end of prohibition their fortunes changed.

Gallo Winery is now the largest family owned winery in the United States and the largest exporter of California wines.

CompanyThe company now employs over 5,000 people worldwide and generates more than $3.4 billion in sales. That’s about 80 million cases of wine shipped each year to more than 90 countries with a product line that includes 60 distinct brands, some of which are shown below.

Information SupportAs is true of any organization its size, Gallo relies on data to manage its operations. So, one could say the Business Analytics is used across the entire organization. But that hardly helps in gaining a better understanding of where and how data is used.

The Value Chain is a good place to start.

The Value ChainThe value chain, a concept developed by Michael Porter, Professor at Harvard Business School, identifies the activities within the organization that create customer value. Shown below, the value chain begins with incoming logistics which for Gallo involves the steps to obtain the necessary inputs for their business processes. Perhaps the most obvious inputs include grapes and other ingredients necessary to produce wine. The value chain continues with the operational processes for producing the wine. Steps involve the crushing and fermentation of grapes.

OutboundLogistics

OperationsInboundLogistics

Sales &Marketing

Value Chain

The Value ChainNext is Sales and Marketing. Here Gallo develops marketing strategies that build brand awareness and create consumer interest in their products. The final activity is called Outbound Logistics and involves those steps necessary to move the product from the winery to distributors and retailers

Together these activities define the primary activities in Gallo’ value chain, but this framework also provides useful insight into all organizations regardless of what they produce and whether they deliver goods or services.

OutboundLogistics

OperationsInboundLogistics

Sales &Marketing

Value Chain

Data and The Value ChainHow does the value chain help us understand organizational data?

Data is necessary to manage and control each and every one of the activities in the value chain. It is used to manage inbound logistics and the supply chains that deliver inputs to the organization. It is used to schedule production and control product quality. It is used to create marketing strategies and monitor sales. And finally, it is used in outbound logistics to manage the shipping process. In a very real sense, data is the glue that holds the activities in the value chain together. It integrates activities across the firm.

OutboundLogistics

OperationsInboundLogistics

Sales &Marketing

Value Chain

Data and The Value ChainBut most important, the concept of a value chain helps us understand that the type of data needed across the firm is different and depends upon the activity it supports. The data needed for inbound logistics is different from the data needed for sales and marketing as is the data needed for every one of the other activities.

The danger, however, is that data is maintained in “silos” within each of these primary activities. So data for inbound logistics might be inaccessible to those in operations. Silos inhibit integration! To avoid this, firms implement Enterprise Resource Planning (ERP) systems, that not only store data used in these activities but make it accessible to managers and decision makers across the entire organization.

OutboundLogistics

OperationsInboundLogistics

Sales &Marketing

Value Chain

Internally Generated DataThe concept of a value chain helps understand where data is used across the organization and the significance of integration. Next we will consider how it is collected and used.

Data is collected in basically two very different ways; Internally and externally. First, it is generated and collected as the firm engages in its daily business. Data for inbound logistics is collected when orders are placed with suppliers. Production/operations data is collected as grapes are crushed and then proceed through the fermentation process. Sales data is collected when distributors or retailers place orders. Shipping and delivery data is collected when the finished product its sent to distributors.

All of these are examples of data that is generated through the primary activities in the value chain. As such, we can call this internally generated data.

Externally Generated DataWhile most of the data available to Gallo in the past had been generated from internal sources, they realized that internal data limited their awareness of competitors and customers. What they needed was to gain access to external data, so they started to be more aggressive in collecting data from wine tasting events and more recently from social media sites.

The Information Pyramid on the right shows these two sources of data, Internal and External.

Internal External

Information Pyramid

Operations Planning and ControlNow consider how these data are used. Internal data are primarily used to plan and control day-to-day operations. This is the second layer in the information pyramid and called Operations Planning and Control. For example, internal inventory data is used by Gallo to determine when grapes need to be ordered. Internal accounting data is used to create financial statements such as a balance sheets and Profit and Loss statements. And internal data is used to review sales patterns for each of their products and create production schedules. But these are only a few examples of how they use internal data to plan and control their operations.

Internal External

Operations Planning and

Control

Information Pyramid

StrategicThe top of the pyramid represents the use of data in strategic planning. Here, decisions are made, for example, to develop new products, discontinue unprofitable ones, undertake research to improve production methods, and make business procedures more efficient. These are the decisions that affect organizational performance over the next several years as contrasted with operations planning and control decisions that affect performance over the next several months.

Internal External

Operations Planning and

Control

StrategicPlanning

Information Pyramid

StrategicBoth internally and externally generated data are used at the strategic planning level, but when the source is internal, the data is highly aggregated or summarized. There is little need to access detailed sales records for a distributor. Instead, the interest would be, for example, in the total number of cases shipped to a distributor by month over the last year.

Using externally generated data, as another example, Gallo’s market share would be compared with other wineries. Internal External

Operations Planning and

Control

Information Pyramid

StrategicPlanning

Data Flow Within the PyramidOften this highly aggregated data representing both internally and externally generated data is displayed on a dashboard, a method of presenting data visually that combines several critical success factors on one screen. So top-management might view sales of their top five products over the last six months, production costs over this period, market share and sales by region.

From this aggregated view of critical factors management is in a better position to make decisions about production levels, new product development projects and marketing strategies.

Transaction Systems

Operational Management and Control

StrategicPlanning

Role of Business AnalyticsThe challenge in Business Analytics is to use both internally and externally generated data to provide the kind of information that management needs to effectively manage the value chain.

To meet this challenge the tools we use in Business Analytics must be capable of supporting decisions at the management planning and control as well as the strategic planning levels. Sometimes, very basic statistical tools are all that is needed to make sense of the data. It might be as simple as computing an average or plotting monthly sales over a one year period. At other times more sophisticated tools are required to better understand data relationships, uncover opportunities and provide useful information in managing the value chain.

Here are several examples of how Gallo is using Business Analytics to help their managers make better sense of the data that is available to them.

Marketing – Consumer TastesTo develop the kind of strategic marketing plans that can further improve Gallo’s position in a very competitive marketplace it is necessary to understand, as thoroughly as possible, consumer tastes. To meet this challenge Gallo maintains aggressive programs directed at collecting consumer data. At tasting events and tasting rooms in their California and Washington vineyards the marketing group is not simply hosting an event to gain a few customers. Rather, those who attend are asked questions the answers to which then serve as resource to mined.

The problem is that customers are not the same. Each one has different tastes or preferences. Accordingly, the challenge is to differentiate customers rather than assume they represent a homogeneous group.

But how can they be differentiated? To make sense from their data, especially the comments collected at tasting events, Gallo has identified clusters, also called segments, into which consumer can be assigned.

Marketing – Consumer TastesBased upon the data they have collected, five core customer clusters have been identified. They include:• Sweet and Fruity• Light Body and Fruity• Medium Body and Rich Flavor• Medium Body and Light Oak• Full Body and Robust Flavor

Marketing – Consumer TastesThese clusters can then be used to organize customer comments at future tasting events into one or more of these clusters. In this way Gallo can monitor trends. For example, the number of tasters preferring Sweet and Fruity may decline over several months while the number preferring Medium Body and Light Oak may increase. Clusters thereby overcome the shortsighted approach where the consuming population is considered homogeneous. Using this new approach, not only can movement across clusters be monitored but promotions can be targeted to a specific cluster.

Marketing - Social MediaIn recent years Gallo has discovered that an increasing volume of potentially useful data can be found on social networking sites like Facebook and Twitter. In 2010 they implemented a social media listening platform where they now scan for product related comments.

When a relevant comment is found, the data is added to Gallo’s social network database. Relevant comments are identified by finding mention of their name and then scanning a hierarchy of key words such as “bitter“ “smooth” “Right price” “Quality” “Aromatic” “Too sweet” “Love it” “Will buy again” or Will not buy again”. Then, they analyze the number of relevant comments and relate them to the number of bottles sold. By monitoring this data over time they are able to further improve their ability to detect trends and thereby help support the decisions that their operations, marketing or product development teams must make.

Marketing -MerchandisingThe collection of data and the use of statistics extends to distributors and retail stores that carry their products. Merchandising strategies like end-of aisle displays are tested, as are store shelf signs, and "necker" signs that hang from the neck of a bottle. Consumers are brought in to "shop" virtual shelves, allowing Gallo test a variety of merchandizing approaches while avoiding the cost and delays of in-store testing. By using an approach known as A/B testing they can compare strategies and limit the risk of implementing strategies that produce disappointing results. Then, with the evidence from their A/B tests they advise retailers on the best ways to display their wines.

Operations - Quality ControlAnother activity in the value chain where business analytics is used is operations.

If customers complain about the variation in taste form one bottle to another, or if they generally complain about taste, this data is collected and summarized. The source may be customer support lines, email, restaurants that serve their wine, and more commonly, comments made on social media. When it has been determined that there is merit to these complaints, the quality assurance team is alerted and the route source of the problem is identified.

Operations - Quality Control

Before Social Media it may have taken weeks or months before the company received enough feedback to know that a problem existed and that some action was necessary. Now, the response time has been significantly reduced. The result is better control and, above all, a more proactive approach to protecting Gallo’s brand.

Operations – Improving ProcessesWatering is an important factor in growing grapes. It turns out that uniformly watering and fertilizing across an entire vineyard may not be an optimal watering strategy. The reason is that variations in soil characteristics can result in the production of grapes whose quality varies.

Gallo studied innovative sensing technologies with the goal of increasing the quality and quantity of its crops while maintaining sustainable irrigation and fertilization practices.

Operations – Improving ProcessesUsing evidence from this study Gallo initiated new procedures and in a pilot study proved they could reach their objectives. They reduced water consumption by 20 percent while increasing crop yield by 10 to 20 percent. Given the reality of diminishing farms lands and an impending critical shortage of water Gallo proved, once again that answers can be found through experimentation, new ideas and evidence based analysis.

An Evidence Based CultureWhat should become apparent from this very brief case study is that Gallo has created an evidence-based management culture, one in which decisions across the value chain are supported by using both internal and external data. While internal data tends to be more convenient, Gallo has also taken the initiative to collect data from customers at wine tasting events as well as monitoring social media to further its understanding of the markets in which they compete. But above all, it is a company that recognizes that data is an asset to be properly managed and used just as any other asset.

While Gallo might not be considered an analytical innovator they are certainly not analytically challenged.