Analytics at Work - how to make better decision and get better results

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<ul><li><p>8/3/2019 Analytics at Work - how to make better decision and get better results</p><p> 1/6</p><p> 2010 Harvard Business School Publishing. Created for Harvard Business Review by BullsEye Resources www.bullseyeresources.compowered by</p><p>Aay a W</p><p>hoW to mAke better decisionsAnd get better results</p><p>featuring t davp</p><p>February 2, 2010</p><p>key learning summary</p><p>in collaboration with</p></li><li><p>8/3/2019 Analytics at Work - how to make better decision and get better results</p><p> 2/6</p><p>HARVARD BUSINESS REVIEW WEBINARS</p><p> 2010 Harvard Business School Publishing. Created for Harvard Business Review by BullsEye Resources</p><p>Analytics at WorkHOW TO MAKE BETTER DECISIONS AND GET BETTER RESULTS</p><p>Tom Davenport, Presidents Chair in Information Technology and Management, Babson College</p><p>Angelia Herrin, Editor for Research and Special Projects, Harvard Business Review</p><p>OVERVIEW</p><p>Most organizations have massive amounts of data but fail to</p><p>use it in a meaningful way. But with the proper analytical</p><p>capabilities, culture, and business processes, organizations</p><p>can use analytics to achieve their desired resultmaking</p><p>better decisions.</p><p>Organizations can benefit from identifying their key strategic</p><p>and tactical decisions, assess how well they are doing at</p><p>making these decisions, determine which ones can be made</p><p>better, and then institutionalize more analytical decision-</p><p>making processes.</p><p>CONTEXT</p><p>Professor Davenport discussed the key concepts from his</p><p>latest book titledAnalytics at Work: Smart Decisions,</p><p>Better Results.</p><p>Dr. Davenports previous book, Competing on Analytics,</p><p>focused on companies using analytics to create</p><p>competitive advantage. In contrast,Analytics at Work is</p><p>designed to help any organization become more analytical</p><p>and fact-based. This book also emphasizes the important</p><p>linkage between analytics and decision making.</p><p>KEY LEARNINGS</p><p>There is much wrong with decision making.</p><p>In many organizations, there are huge investments in data</p><p>warehousing, ERP, and reporting, but this data isnt used to</p><p>make better decisions. Bad decision processes and outcomesabound. The body of knowledge on good decision making is</p><p>often ignored, and decisions often take too long. There is an</p><p>over-reliance on intuition and an under-reliance on data and</p><p>analytics. There is also little measurement of decision</p><p>processes and outcomes and little accountability for</p><p>decisions.</p><p>Both decision outcomes and processes areoften bad.</p><p>Tom Davenport</p><p>From the financial crisis to the decisions to invade Iraq and to</p><p>stay in Vietnam, there are numerous examples of bad</p><p>decision processes and outcomes in both the private and</p><p>public sector. And, even though massive amounts of dataexist, organizations continue to have bad decision processes</p><p>and make bad decisions. (While a good decision process</p><p>doesnt guarantee a good outcome and bad process doesnt</p><p>assure a bad outcome, there is a correlation.)</p><p>The good news: there are significant opportunities to improve</p><p>decision making. Analytics and algorithms can lead to better</p><p>decisions, as can the wisdom of crowds. Use of behavioral</p><p>economics can improve decision making and some decision</p><p>making can be automated. However, to date most</p><p>organizations havent taken advantage of the opportunities</p><p>that exist to improve their decision making.</p><p>A model exists for making better decisions.</p><p>The model shown below is designed to deliver better</p><p>decisions. It starts with a foundation of analytical capabilities,</p><p>creates an organizational context, delivers better decisions,</p><p>and then entails a systematic review to continuously improve</p><p>the decision process.</p></li><li><p>8/3/2019 Analytics at Work - how to make better decision and get better results</p><p> 3/6</p><p>Harvard Business ReviewWebinarsAnalytics at Work: How to Make Better Decisions and Get Better Results</p><p> 2010 Harvard Business School Publishing. Created for Harvard Business Review by BullsEye Resources</p><p>Analytical Capability</p><p>Professor Davenport has identified organizations at five</p><p>stages in developing their analytical capabilities. This ranges</p><p>from the analytically impaired (Stage 1) to analytical</p><p>competitors (Stage 5).</p><p>The capabilities required for any organization to become</p><p>more analytical follow the D.E.L.T.A. model.</p><p>Data. This is the prerequisite for analytics. At a minimum,</p><p>data must be clean, common, integrated, and accessible in a</p><p>central data warehouse. Organizations can realize advantage</p><p>by having data that competitors dont. This entails</p><p>measurements that are new, distinctive/proprietary, and</p><p>important. For example, Marriott has proprietary metrics on</p><p>revenue optimization and Harrahs measures employee</p><p>smile frequency, which predicts customers experiences.</p><p>Collect data in areas that others havent</p><p>addressed and then apply this data analyticallyin decision making.</p><p>Tom Davenport</p><p>Enterprise. To become more analytical, organizations must</p><p>go beyond managing data locally or in silos. Successful</p><p>analytical competitors manage their data and analytics</p><p>program at an enterprise level. They create enterprise-wide</p><p>analytical capabilities and invest in enterprise-scale analytical</p><p>technologies.</p><p>Leadership. This is the most critical trait of analytical</p><p>companies, and remains extremely rare. Organizations that</p><p>become more analytical have leaders who fully embrace</p><p>analytics and lead the companys culture toward fact-based</p><p>decision making. Quotes of such leaders include, Do we</p><p>think or do we know? and In God we trust; all others bring</p><p>data.</p><p>Targets. With limited analytical resources, analytical</p><p>organizations pick a primary strategic target for their initial</p><p>analytical efforts (such as marketing or supply chain) as well</p><p>as a secondary target. Over time, the use of analytics and</p><p>analytical decision making will expand in an organization.</p><p>But long-term success starts with a specific strategic</p><p>application.</p><p>Analysts. An organization cant become more analytical</p><p>without analytical people. The types of analytical talent</p><p>required include: 1) Champions, who lead analytical</p><p>initiatives (perhaps 1% of the organization); 2) Professionals,</p><p>who can create new algorithms (5-10%); 3) Semi-</p><p>professionals, who can use visual and basic statistical tools(15-20%); and Amateurs, who use spreadsheets (70-80%).</p><p>Organizations need each of these types of analysts.</p><p>A table on Exhibit 1 fromAnalytics at Work shows how</p><p>organizations progress from Stage 1 to Stage 5 of each of the</p><p>success factors in the D.E.L.T.A. model.</p><p>Organizational Context</p><p>The context needed to become more analytical includes</p><p>creating an analytical culture and having analytical business</p><p>processes:</p><p>Analytical culture. An analytical culture is one where use of</p><p>facts, evidence, and analysis is the primary way of making</p><p>decisions. There is still room for intuition, but intuition</p><p>should be based on experience and expertise. In analytical</p><p>cultures, it is okay to push back by asking, Wheres your</p><p>data? When facts are lacking, organizations with analytical</p><p>cultures emphasize testing and learning, and they focus on</p><p>action after analysis.</p><p>Analytical processes. Becoming more analytical also entails</p><p>thinking very analytically about an organizations business</p><p>processes. This entails mapping out key processes, such as</p><p>the ordering processes, and understanding all possible steps</p><p>in the process. Analytics can be used to understand which</p><p>customers are most valuable and what actions might be taken</p><p>to improve the process. Today it is rare for organizations to</p><p>be highly analytical regarding their business processes.</p></li><li><p>8/3/2019 Analytics at Work - how to make better decision and get better results</p><p> 4/6</p><p>Harvard Business ReviewWebinarsAnalytics at Work: How to Make Better Decisions and Get Better Results</p><p> 2010 Harvard Business School Publishing. Created for Harvard Business Review by BullsEye Resources</p><p>Desired Result</p><p>The goal for analytics is to make better decisions. However,</p><p>while many organizations collect data and some</p><p>organizations engage in analytics, few organizations link their</p><p>analytics activities to their decision making.</p><p>Better decisions are the goal of analytics.</p><p>Tom Davenport</p><p>In a study of decisions, Professor Davenport found that 90%</p><p>of companies made at least some effort to improve a specific</p><p>decision. The decisions that organizations looked to improve</p><p>tended to be those that were frequent and operational, such</p><p>as pricing decisions, targeting decisions, merchandising</p><p>decisions, and location decisions.</p><p>A system for improving decisions should include the</p><p>following steps:</p><p>Identify. This entails identifying the organizations key</p><p>strategic and tactical decisions, which rarely occurs in most</p><p>organizations.</p><p>Inventory. Determine how well the organizations key</p><p>decisions are being made today. What processes and tools are</p><p>being used? Are the key decisions being made intuitively or</p><p>analytically?</p><p>Intervene. Based on identifying the key decisions and</p><p>conducting an inventory of how they are being made,</p><p>determine if a decision intervention is requireddoes the</p><p>organization need to change how certain critical decisions are</p><p>being made? Are better people, processes, and tools required?</p><p>(Use of analytics is the most common intervention that</p><p>organizations make to improve their decision making).</p><p>Institutionalize. Allocate resources (people and technology)</p><p>and create processes to institutionalize how the</p><p>organizations key decisions are made.</p><p>Systematic Review</p><p>An important step in improving an organizations analytical</p><p>capabilities is to close the loop by engaging in a review of an</p><p>organizations key decisions. Many successful organizations</p><p>look back at all major decisions to assess the quality of the</p><p>decision process and the outcome. They look closely at any</p><p>errors that are made and seek to rectify these mistakes in</p><p>OTHER IMPORTANT POINTS</p><p>Building organizational support. Getting leadership support</p><p>for analytics and more analytical decision making can be a</p><p>challenge, yet leadership support is critical. Find a senior</p><p>executive who is analytical and enlist this person as a partner</p><p>in getting the analytical movement going.</p><p>The role of intuition. Intuition can play an important role in</p><p>generating the hypotheses that analysts investigate and in</p><p>deciding when analysis may not be appropriate.</p><p>Preventing slow decisions. Organizations can measure how</p><p>long decisions take and if they are taking too long, can</p><p>investigate to understand why, and can reengineer the</p><p>decision process.</p><p>Basing KPIs on analytics. In many organizations key</p><p>performance indicators (KPIs) are set arbitrarily. By using</p><p>analytics, KPIs can be established based on facts.</p><p>Analytical measures and incentives. Some organizations are</p><p>beginning to measure and reward managers for their decision</p><p>processes; not just for the outcomes of their decisions, which</p><p>can be delayed by many years.</p><p>Analytics for small businesses. Analytics is not just for large</p><p>enterprises; small organizations can also use analytics to</p><p>make more fact-based decisions. Technology is not the</p><p>barrier. Software as a service is increasingly making</p><p>analytical tools available to small businesses. The biggest</p><p>obstacle is analytical people. However, even such people canoften be rented.</p><p>New analytical organization. A new peer-based research</p><p>organization has been formedthe Inter-national Institute</p><p>for Analytics (IIA). IIA is a community of analytics</p><p>practitioners that will conduct research and gather</p><p>information on how real-world organizations are deploying</p><p>analytics. It is a way to advance the profession of analytics</p><p>and analytical decision making. All individual members who</p><p>join IIA in February will receive a complimentary</p><p>autographed copy of Analytics at Work. Go to</p><p> to learn more or join.</p><p>Recommended reading. In addition to his own books,</p><p>Professor Davenport suggested reading How We Decide by</p><p>Jonah Lehrer and Nudge by Richard Thaler and Cass</p><p>Sunstein.</p></li><li><p>8/3/2019 Analytics at Work - how to make better decision and get better results</p><p> 5/6</p><p>Harvard Business ReviewWebinarsAnalytics at Work: How to Make Better Decisions and Get Better Results</p><p> 2010 Harvard Business School Publishing. Created for Harvard Business Review by BullsEye Resources</p><p>EXHIBIT 1</p></li><li><p>8/3/2019 Analytics at Work - how to make better decision and get better results</p><p> 6/6</p><p>Harvard Business ReviewWebinarsAnalytics at Work: How to Make Better Decisions and Get Better Results</p><p> 2010 Harvard Business School Publishing. Created for Harvard Business Review by BullsEye Resources</p><p>BIOGRAPHIES</p><p>Tom Davenport</p><p>Presidents Chair in Information Technology and Management, Babson College</p><p>Tom Davenport holds the President's Chair in Information Technology and Management at Babson College. His books and</p><p>articles on business process reengineering, knowledge management, attention management, knowledge worker productivity, and</p><p>analytical competition helped to establish each of those business ideas. Over many years he's authored or co-authored nine</p><p>books for Harvard Business Press, most recentlyCompeting on Analytics: The New Science of Winning (2007). His next book,</p><p>Analytics at Work: Smarter Decisions, Better Results, will be published in February 2010. Davenport has authored fifteen</p><p>articles forHarvard Business Review. His byline has also appeared for publications such asSloan Management Review,</p><p>California Management Review, Financial Times, Information Week, CIO, and many others.</p><p>Davenport has an extensive background in research and has led research centers at Ernst &amp; Young, McKinsey &amp; Company, CSC</p><p>Index, and the Accenture Institute of Strategic Change. Davenport holds a B.A. in sociology from Trinity University and M.A. and</p><p>Ph.D. in sociology from Harvard University.</p><p>Angelia Herrin</p><p>Executive Director of Project Development, Harvard Business Review</p><p>Angelia Herrin is executive director of business development at Harvard Business Review. At Harvard Business Review, Herrin</p><p>oversaw the re-launch of the management newsletter line and established the conference and virtual seminar division for</p><p>Harvard Business Review. More recently, she created a new series to deliver customized programs and products to organizations</p><p>and associations.</p><p>Prior to coming to Harvard Business Review, Herrin was the vice president for content at, a Web site</p><p>focused on women business owners and executives.</p><p>Herrins journalism experience spans twenty years, primarily with Knight-Ridder newspapers and USA Today. At Knight-</p><p>Ridder, she covered Congress, as well as the 1988 presidential elections. At USA Today, she worked as Washington editor,heading the 1996 election coverage. She won the John S. Knight Fellowship in Professional Journalism at Stanford University in</p><p>198990.</p><p>The information contained in this summary reflects BullsEye Resources, Inc.s subjective condensed summarization of the applicable conference session. There may bematerial errors, omissions, or inaccuracies in the reporting of the substance of the session. In no way does BullsEye Resources or Harvard Business Review assume anyresponsibility for any information provided or any decisions made based upon the information provided in this document.</p></li></ul>