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Anatomy of the new decision


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Anatomy of the new decision

  1. 1. Anatomy of the New DecisionHow Five Hot Trends Are Shaping the Future ofBusiness AnalyticsA White PaperWebFOCUS iWay SoftwareWebFOCUS iWay Software
  2. 2. 1 Introduction 3 Predictive Analytics: Back to the Future 3 Predictive Modeling and Analytics 5 Outsourced Data for Better Insights 6 (I Love Analytics) for Sentimental Reasons 8 Big Decisions Require Big Data 9 Mobile BI: BYOD FTW 11 Anatomy of the New Decision 11 Law Enforcement 12 Retail 13 Solutions From Information Builders 13 Intelligence 13 Integration 14 Integrity 15 ConclusionTable of Contents
  3. 3. Information Builders1IntroductionFor decades, companies have made decisions based on instinct, hunches, and intuition. Thencame business intelligence (BI), which made decision-making more scientific. Before it was knownas BI, it was referred to as “decision support.” Companies would review the data they had collectedand make decisions about the future based on what had happened in the past. For example:■■ A two-year, increasing trend of sales in Florida dictates the need to increase inventory levels overlast year in that region to meet demand■■ A law enforcement agency deploys more of its officers to District A, one its highest crime areas■■ Students with higher SAT scores have higher graduation rates than students with lower scores,so to improve graduation rates, a university only accepts students with higher SAT scoresThat kind of thinking was good – once. Nowadays, it’s like fighting with one hand tied behindyour back.Each of the decisions above was made using a small number of data points to conjure up anoverly simplistic conclusion. Smarter decisions would incorporate more relevant data that answersmore sophisticated questions, such as:■■ What products or services have Florida customers been most positive about on socialnetworking, blogs, and free-form feedback sites?■■ What factors – such as weather, special events, and economics – influence various types ofcrimes and where they are likely to occur today?■■ What are the likely consequences of increasing the average SAT score in the acceptance process?The good news is that exciting technologies are now emerging, and in some cases, converging,to help organizations drive innovation, which empowers people to make smarter decisions withinsight based on more than just structured, static data. Behind the tech industry buzzwords,there are practical and proven methods for applying these new technologies to your currentinformation management strategy and unlocking measurable returns:■■ Cloud-based information services enable us to get information that a company might not havepreviously tracked on its own, such as demographic and market changes in Florida■■ Predictive analytics combines many factors to present a clear picture of what’s most likely tohappen, what is the best-case scenario, and what action should be taken■■ Social media analytics help us to understand how other people are reacting to our actions – farmore quickly and reliably than focus groups would■■ Big data technologies help us to manage the increasing velocity, variety, and volume (the threeVs) of all of the data that makes this possible■■ Mobile computing deploys analytics to more people, so they can make smarter decisionswhenever and wherever they are
  4. 4. Anatomy of the New Decision2Moreover, the technology advancements are more effective when used in concert than whentaken separately.In this paper, we will discuss how cloud-based services, predictive analytics, social media analytics,big data, and mobile computing are combining to take business intelligence beyond traditionalboundaries and transform the way critical decisions are made. We will also highlight InformationBuilders’ solutions and share two use cases, which demonstrate how two organizations – a lawenforcement agency and a retailer – might use available tools and technologies to tap into thewealth of information available.
  5. 5. Information Builders3Queries, reports, dashboards, and other forms of business intelligence are often used to answersimplistic questions: What product mix was sold this month compared to last month? What arethe year-over-year overhead expense trends?OLAP and query tools have allowed users to refine and enrich those comparisons, but while thetools have gotten better, faster, and easier to use, the basis for how they facilitate decision-makingbased on historical data hasn’t changed much.Predictive analytics changes the game by going beyond an analyst’s current viewpoint andproviding new, sophisticated insight about how the past can help predict the future.Predictive Modeling and AnalyticsPredictive analytics is often misunderstood. It doesn’t conjure up miraculous forecasts from thinair. Instead, it correlates the relationships between many factors (most commonly descriptivedimensional and numeric data) and provides insight into which of those factors may influencean outcome. That influencing effect can then be given a score or a probability, which becomes a“predictive analytic.”The choice of factors affects decision-making the most. For instance, scouting in baseball hasalways been based on metrics such as stolen bases, RBI, and batting average, but it took thestatistical analysis headed up by Billy Beane, general manager of the Oakland A’s, to recognize thaton-base percentage and slugging percentage were more predictive markers of offensive success.Predictive Analytics: Back to the FuturePredictive data mining supports retail initiatives such as target marketing,cross- and up-selling, and customer acquisition and retention.
  6. 6. Anatomy of the New Decision4Beane could find those qualities more cheaply on the open market, and was thereby able toassemble a team competitive with the best in the league – for about a third of the payroll cost.Convenience store transactions might be affected by weather, with in-store ATMs generatingwalk-in traffic when outdoor ATMs are less pleasant to use. Used car sales might be affected bythe local real estate rental market. Generic medication prescriptions might see an uptick after amarketing campaign by a brand-name pharmaceutical company.The point isn’t that any one of these things is true or false; it’s that you wouldn’t know whetherthey were true or false unless you assembled the data and found out where the statisticalcorrelations are. That modeling, and the predictions that come from it, lead to business value.
  7. 7. Information Builders5With predictive analytics, it can be a challenge to collect enough data while ensuring its relevanceto outcomes. For example, many organizations have failed to collect certain historical data outsidetheir own sphere of influence – but that external or third-party data may have a significantinfluence on their outcomes. After all, who would expect weather to impact retail sales or crimerates? Why would a company collect stock market trends or changes in tax rates to see if theyaffect automobile sales?But these factors really can affect business results. When the marketing arm of a national retaileranalyzes how sales were affected by a Presidents’ Day promotional campaign – but doesn’t takeinto account a serious storm system in the southeastern U.S. – it might reduce its efforts in Floridawhen it should be increasing them.This problem isn’t limited to predictive analytics, either. Any form of analytics will be limited by theavailable data.Fortunately, there are information providers for almost any kind of information you can think of,and cloud-based web services allow users to unify historical data with information about theweather, crime, the stock market, travel trends, taxes, and virtually anything else. Integrating cloud-based external data resources with unstructured input from social networks enables companies todramatically improve the sophistication of their decision-making without having to collect everypossible external factor that might affect their businesses.Outsourced Data for Better Insights
  8. 8. Anatomy of the New Decision6Sellers used to have a chance to talk to potential customers before they made a decision aboutwhat product to buy. Those days are gone. In business-to-business sales, more than 60 percent ofa typical purchasing decision now happens before the buyer ever contacts a supplier.1Buyers aren’t talking to sellers because they’re talking to each other. Social networks and blogshave made it very easy for them to get information about products and services that interestthem. It’s incredibly important for businesses to discover what they’re thinking about theirproducts, services, marketing campaigns, salespeople, return policies, customer support, andanything else that reflects on them. In other words, they need the ability to do sentiment analysisabout their company, brands, executives, and campaigns.One influential person tweeting “[brand] is horrible!” can have a devastating effect. A few dozenFacebook posts complaining about on-hold times or product limitations can deter future buyers.On the other hand, a vibrant customer community that is nurtured to provide positive statementswill move potential customers into the buyers’ camp. A brand that listens and responds tocustomer issues with honesty and transparency can establish even closer relationships basedon trust.PepsiCo is a great example of a company that understands the power of social insight. It has usedsocial networks to gather customer insight about its DEWmocracy promotions, which have led tothe creation of new varieties of its Mountain Dew brand. Since 2008, the company has sold morethan 36 million cases of them2.The best news of all is that companies can now analyze sentiment continuously, at a fraction ofthe cost of other methods, while incorporating sentiment information into other forms of analysis.Social media sentiment analysis can replace or augment $15,000 phone surveys, $7,000 mailsurveys, and $6,000 focus groups – while catching problems before they get out of control.(I Love Analytics) for Sentimental ReasonsAccurately understand customer sentiment and visualize the context of thewords used to describe your company, products, and services.
  9. 9. Information Builders7As Forrester’s Zach Hofer-Schall says, “Social media’s prevalence across the web gives consumersand brands a new way to connect online. But while most businesses know the importance ofsocial media, most are missing opportunities by not capturing and analyzing the data generatedin social channels.”3Imagine how different the analysis of a Presidents’ Day promotion might look if, instead of justlooking at the timing of the promotion, it also took into account both the weather and thesentiment of tweets that contain a related hashtag. Understanding social engagement through anintegrated use of data, tools, and technologies is a clear priority for all organizations for amplifyingcustomer loyalty, competitive differentiation, and growth.1 Adamson, Brent; Dixon, Matthew; Toman, Nicholas. “The End of Solution Sales,” Harvard Business Review,August 2012.2 Dival, Roxane; Edelman, David; Sarrazin, Hugo. “Demystifying Social Media,” McKinsey Quarterly, McKinsey Company, April 20123 Hofer-Shall, Zach. “Leverage Social Data To Elevate Customer Intelligence,” Forrester, May 2012.
  10. 10. Anatomy of the New Decision8Data volumes are growing rapidly, for many reasons. Predictive analytics are most reliable onvery large data sources. Blog posts and social media can encompass a huge amount of language.Sensor data (everything from smart utility meters in your house to RFID chips in warehouses) hasmade certain things possible, while increasing data volumes dramatically. The mobile channel hasspawned a whole new category of data to track, from in-app clicks to mobile transactions.And that just accounts for one of the “three Vs” of big data.A recent study by the Economist Intelligence Unit, commissioned by Capgemini, found thattwo-thirds of respondents – 607 global executives (43 percent of them C-level and boardexecutives) from 20 different industries – say that the collection and analysis of data underpinstheir firm’s business strategy and day-to-day decision-making. In fact, just more than half say thatmanagement decisions based purely on intuition or experience are regarded as suspect.4Because there seems to be value in big data, many companies start collecting massive volumes ofdiverse, real-time data before they know what to do with it. Unfortunately, they don’t necessarilymake sure that it’s clean at collection time. Ideally, data is clean as transactions flow into yoursystems, such as when the user clicks “OK” on your website or as an RSS feed tells you that a newblog post is live.Moreover, having data quality tools helps to correlate information from multiple systems. Forinstance, companies may improve their one-to-one marketing dramatically if they can determinethat “jdoe1968” on their website is “Jonathan Doe,” who used a credit card on the phone lastmonth and also identified himself as “Jon Doe” just now when he entered a store in Manhattan.Finally, if a company’s data is truly big, most people will need help in finding the information oranalytics that derive from it. They’ll need a search engine that’s fully populated with structureddata, unstructured data, and links to existing reports and analysis.Big Decisions Require Big Data4 Olavsrud, Thor. “Big Data Analytics Today Lets Businesses Play Moneyball,” CIO, August 2012.
  11. 11. Information Builders9The new decision isn’t chained to a desk.Information is our constant companion: at meetings, in coffee shops, or first thing in the morningif that’s when we need it. How we interact with information can be very personal – so muchso that we now expect to interact with our personal laptops, smartphones, and tablets to getanswers to business questions. As a result, it’s more important than ever that business intelligencebe available on any device, whether iOS, Android, or BlackBerry, and in virtually any form factor.There are a couple of ways that the mobile channel impacts decision-making and, whencombined with a few of the other tech trends we’ve discussed, can be a total game changer.First, mobile apps can be designed to empower your employees with real-time information –and the ability to analyze that information on the fly and on the go. By optimizing data analyticsfor mobile platforms, and incorporating the native capabilities of the mobile devices, youare empowering users, creating a personal connection to your brand for all key stakeholders,improving efficiency, streamlining communications, and differentiating your services.But there is also a “back-office” side to mobile that can improve our understanding of ourbusiness so that we make better strategic decisions about its operations, marketing, and finances.Smartphones are essentially sensors that enable you to get location- and context-aware feedbackfrom a variety of touchpoints in real time. When you combine this mobile data with otherdata sources (i.e., big data) and apply analytics, the result is a whole new understanding of theworkforce, the customer, and the market.Mobile BI: BYOD FTWMobile BI enables you to check critical data at any time, from any location.
  12. 12. Anatomy of the New Decision10Interestingly, this increased emphasis on mobility also increases the emphasis on data quality.When someone shares information with a lot of people, it had better be right. And since mobiledata also needs to come from every kind of system so people don’t have to wait to get to theirdesks to get the real answer, mobile applications also increase the need for data integration.
  13. 13. Information Builders11The new decision – one that leverages predictive analytics, as well as data from cloud andsocial media sources – applies to many real-world scenarios. From financial institutions tryingto put together the most successful portfolio of products and services to telecommunicationscompanies seeking new and effective ways to increase loyalty, the new decision provides insightthat can drive competitive advantage.Lets look at two potential use cases – one in law enforcement and another in retail.Law EnforcementThe image above represents a city divided into six sectors. Each sector is color-coded based onhistorical crime data: Sector B has the highest crime rates, followed by sectors C, F, D, E, and A.Standard historical crime analysis would indicate that the police dispatcher would need to put thegreatest police presence in sector B to help deter crime. However, today’s event calendar showsthat there is a free concert in sector A. The concert starts at noon in the city park, with 5,000attendees expected, but the weather forecast shows a 60 percent chance of rain. This typicallymeans that there will be at least a 50 percent drop-off in concert attendance.In the past, when the forecast has called for rain, the crimes that commonly occur in sector B tendto decrease, while occurrences of petty theft in the shopping mall parking lots in sector F increase.Anatomy of the New DecisionABCDEF
  14. 14. Anatomy of the New Decision12A look at public sentiment on the city’s Facebook page, as well as on various local blogs, showsthat many people are concerned with the high number of traffic accidents taking place on themain highway leading into the city in sector E. An astute analyst also notices that activity on theband’s Facebook page (the band playing the free concert) suggests that there is going to be an“after party” at one of the nightclubs near the concert in sector A – meaning additional police maybe needed hours after the concert concludes.This information shouldn’t automate every decision the dispatcher makes – people should stillbe in control of critical decisions – but it can crystallize the factors that should affect his choices.Predictive scoring may tell him that he needs more coverage in sector A at the concert and nearthe after party hours later, and he’ll choose to fulfill that need with foot patrols. Meanwhile, he’llreallocate traffic police to cover sector E on the highway, and deploy police on bicycles in sector Fin the parking lots of the shopping mall.RetailA large retailer sells an average of 100 cases of water each week. However, predictive modelsthat include weather data show that stores in the southwest will sell nearly twice as many caseswhen temperatures soar above 90 degrees. Since temperatures are expected to be high for thenext week, the retailer can adjust its forecasts accordingly. The same retailer has also found thatoutlets within five miles of a large body of water (where boating is a common pastime) tend tosell nearly three times as many marine-grade nuts, bolts, and fasteners as outlets in other areas.This information was discovered using a web service that provides maps and distances for specificaddresses and points of interest.Store managers can also monitor a real-time dashboard that displays recent posts on thecompany’s Facebook page. These posts are solicited via a large sign at each checkout counter,asking shoppers to comment on their experience. The dashboard allows managers to track salesand shopper sentiment, so they can quickly adjust staffing and labor levels accordingly, to ensureoptimum service.The bottom line is that making decisions is not always a black-and-white, yes-or-no effort.A decision itself can be a complex array of smaller decisions that combine to produce adesired result.Information shouldn’t automate every decision – people should stillbe in control of critical decisions – but it can crystallize the factors thataffect those decisions.
  15. 15. Information Builders13Information Builders designs and develops high-value solutions that help companies to boostrevenue by providing unmatched integration of enterprise information assets, dramaticallyimproving the integrity of the data contained in those assets, and transforming that data intopowerful intelligence for wide-scale use.IntelligenceThe WebFOCUS BI platform combines broad data access with unparalleled usability, scalability,and low cost of ownership to make information and analytics readily available and easilyconsumable to an unlimited number of internal and external users. WebFOCUS features:■■ Powerful BI that makes reports, queries, and dashboards available to power and business users■■ Advanced analytics, visualization, location intelligence, and enterprise search to enable accuratecustomer analysis, revenue forecasting, price simulation, and more■■ Comprehensive performance management that aligns strategy with key performance indicators(KPIs), and balances them against risk■■ The ability to build once, and deploy across all online and mobile channels for a consistent userexperience■■ Innovative sentiment analysis to help companies mine data from social media sites, and analyzeit to accurately assess customer opinionInformation Builders’ Intelligence solutions also offer unparalleled scalability, reliability, and ease ofuse. So companies can rapidly and economically create and deploy comprehensive, yet intuitiveself-service systems that meet the information needs of thousands, tens of thousands, and evenmillions of external customers.IntegrationiWay Software Integration solutions from Information Builders help you to collect every kindof information, whether you need it in real time or for historical purposes. iWay supportsunstructured data, such as blog posts and social media streams; cloud-based data from webservices or API queries; structured data from enterprise resource planning (ERP), customerrelationship management (CRM), legacy, and other systems; or sensor data, such as RFID or UPCscans and utility gauge readings. With iWay, organizations can empower real-time decision-making for competitive advantage and revenue optimization. iWay Integration solutions provide:■■ A robust integration infrastructure that allows companies to rapidly and economically buildbroad-reaching integration architectures■■ Data integration solutions that facilitate coordination and cohesiveness across even the mostdiverse and disparate information environments■■ A comprehensive universal adapter suite that contains pre-packaged integration componentsto provide direct, native access to more than 300 sources, including data, applications, B2Binteractions, and cloud-based systemsSolutions From Information Builders
  16. 16. Anatomy of the New Decision14■■ Big data solutions that support high-performance data stores, such as IBM Netezza, OracleExadata, SAP HANA, Teradata and Teradata’s Aster Data, EMC Greenplum, HP Vertica, 1010data,ParAccel, and Kognitio, as well as MapReduce databases such Hadoop and MongoDBWith iWay, it’s easy to take data from every kind of system and bring it to your mobile apps –whether the information is cloistered away in legacy systems or stuck inside proprietary ERP andCRM applications, whether it’s big data or many tiny transactions, and whether day-old data isokay or you need it in real time. The most time-consuming and labor-intensive step of mobile appdevelopment – information integration – is cut short dramatically with iWay Integration solutions.IntegrityiWay Integrity solutions include data quality capabilities that can help you create a data qualityfirewall, ensuring the quality of data before it spreads into other parts of your enterprise. Theresult is better operational processes, better BI, and – as the data moves into the realm of big data– better correlated and managed big data analytics. iWay data integrity solutions also providemaster data management (MDM) technology that can correlate disparate information from verydifferent system types – and can be overseen by data stewards, who can even manage data fromtheir mobile devices. iWay data integrity solutions comprise:■■ Data quality management tools, with an automated rules engine, for creating a real-time dataquality firewall that proactively preserves information integrity■■ Master data management to synchronize disparate data sources and create a single, goldenrecord for each product, customer, patient, or citizen■■ Data governance solutions that provide end-to-end control over how information is managed asit is collected, used, and maintained
  17. 17. Information Builders15The examples in this paper demonstrate how complex effective decision-making can be. Becausea variety of factors influence outcomes, straightforward “yes” or “no” answers simply don’t exist.Every decision is made up of an array of smaller choices, which will impact the eventual result.Decision-makers go through great pains to make sure they have gathered all of the appropriatedata to make a well-informed decision.What is different today is that the new decision can be made with more complete data, moreeasily, and in less time than before. The people making those decisions have the means to takeall influencing factors into account, and weigh them based on their relevance, importance, andimpact. The new capabilities outlined in this paper mean less time is spent gathering data, andmore time is given to mulling over the influencing factors, so they have an appropriate amount oftime to use their experience and intuition to make the best decision.More and more companies are arming their employees with business intelligence tools, likeInformation Builders’ WebFOCUS, and iWay Integrity and Integration solutions, to help them withthese types of data-influenced decisions. And as more and more data – primarily from socialmedia vehicles, mobile channels, and other Internet sources – becomes available for use by thosetools, the accuracy and effectiveness of those decisions will continue to increase rapidly.Conclusion
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