Analytics For Everyone - Even You

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1 White Paper Analytics For Everyone - Even You Abstract Analytics have matured considerably in recent years, to the point that business intelligence tools are now widely accessible outside the boardroom and across lines of business. However, truly sophisticated advanced analytics, which can help with testing ideas, predicting outcomes and creating visuals based on data, have largely remained outside the reach of most people in today s organizations. All too often, we must navigate multiple complex applications or ask someone to produce reports and visualizations. Worse, the output is often too complicated for many of us to interpret and use readily. Now though, a new solution has emerged. IBM Watson Analytics strips away complicated statistical models, technical interfaces, and challenging data preparation so more people can ask critical business questions and get insightful, data-driven answers. Read this paper to learn how Watson Analytics is doing more than broadening access to data and insight It s bringing analytics to every employee, every day. About Ziff Davis B2B Ziff Davis B2B is a leading provider of research to technology buyers and high-quality leads to IT vendors. As part of the Ziff Davis family, Ziff Davis B2B has access to over 50 million in-market technology buyers every month and supports the company s core mission of enabling technology buyers to make more informed business decisions. Copyright 2015 Ziff Davis B2B. All rights reserved.

2 Contents Introduction...3 What Gets In the Way of Analytics For Everyone?...3 What Are We Trying To Analyze?...3 What Do You Want Out Of An Analytics Solution?...4 Focus On Insights, Not the Complexities of Data Management and Analytics...5 Eliminate the Obstacle of Data Preparation...6 Addressing the Skills Gap...6 Let the Cloud Do the Heavy Lifting...7 Don t Keep the Insights To Yourself...7 A Closer Look At Watson Analytics...8 When You Already Know What You Want...8 When You Have a Hunch...8 When You Don t Know Where to Start...8 Conclusion...9 ziffdavis.com 2 of 9

3 Introduction Our ability to collect and analyze data and then make decisions based on powerful insights has exploded in recent years if you have the tools and skills to unlock the information within vast data stores. For too many of us, this means cobbling together data in a spreadsheet or asking IT to build reports and dashboards. Even then, data is often overwhelming and deriving real insights from spreadsheets is challenging at best (and impossible at worst). Yet, we are all hungry for data and information. The desire to be data-driven isn t limited to the C-suite. There needs to be a better way for everyone to not just access data but interact with it and then take action. What Gets In the Way of Analytics For Everyone? Ziff Davis recently surveyed 450 business people like you about their current use of analytics and the challenges they face incorporating analytics into regular decision-making. Not surprisingly, access to data and the ability to analyze data without help from IT or a business analyst topped the list of barriers to more frequent use of analytics. Over 62% of respondents noted that either the complexity of tools or the need to go through other staff and departments got in the way of meaningfully applying analytics to decision making. What are your biggest barriers to using analytics more frequently to inform decision making? Access to the data to do analysis Access to an analytics tool that is simple for me to use Wait time. My organization doesn't have analytics tools I can use without going through IT/business analyst Expense None. We're a data-driven organization Math skills to do analysis Other 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% % Respondants What Are We Trying To Analyze? There are vast amounts of transactional data sitting in a variety of business systems that aren t being leveraged. CRM, ECM, SCM, web analytics, ERP and more can all be used to guide both daily and strategic decisions. Most of us however, can rarely get at the raw data, relying instead ziffdavis.com 3 of 9

4 on reports and dashboards. Even if we can dig deeper than routine reporting might allow, we re still facing an uphill battle. Aggregating the data and then finding relationships between sales data from a CRM system and training data from HR, for example, is rarely something that can happen without input from a dedicated analyst or data manager in IT. This gets at the very nature of ad hoc analysis that most of us attempt every day. The Ziff Davis survey noted above found that nearly 60% of respondents used analytics daily or weekly to make decisions, but the overwhelming majority (70%) used spreadsheets for the task. Often, there is no choice but to pull data manually from reports or dashboards into a spreadsheet, combining it with their own data to derive insights relevant to their specific jobs. We are also beginning to make use of publicly available datasets, ranging from climatic data to information from public transit systems. These types of data rarely make it into standard business intelligence systems, leaving the arduous task of preparing corporate, public, and personal data for analysis. If an accountant has a hypothesis about the relationship between flu outbreaks and sales performance, how can they reliably test their theories and take action to correct sales forecasts based on the data? These are fairly sophisticated analyses in and of themselves, but they represent the sorts of explorations that most of us would happily undertake if we had the right tools What Do You Want Out Of An Analytics Solution? The Ziff Davis survey identified a wide spectrum of analytics needs. Respondents called out sales processes, insight into marketing campaigns, and customer churn as top areas they wanted to improve with analytics, but their interests were as varied as their jobs. This is consistent with anecdotal evidence, but the bottom line is that we all want to be part of what Gartner calls analytic organizations 1 rather than just businesses that use analytics. What do you want to accomplish in your organization with analytics? Improve quality control Improve IT processes and procurement Improve sales processes Improve customer targeting and personalization Assess financial risk Evaluate employee performance Anticipate product demand Improve logistics Gain insight into marketing campaigns Reduce customer churn Improve employee recruitment and retention Anticipate equipment maintenance Other 1. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% % Respondants ziffdavis.com 4 of 9

5 Consumers use a wide variety of data regularly to make decisions. Customer ratings and reviews, opinions from social networks, news, trends, etc., all influence buying decisions. Now these consumers are coming to work and expecting to have that same broad access to data to make work decisions. And why shouldn t they? Business conditions change too rapidly to wait for a report author in IT to Analytics can help drive business forward, but it s up to the individual to use the available data to create new business opportunities. Putting data in the hands of all employees allows innovation to occur. -Gartner, 2015 assemble a dashboard with key metrics. More significantly, many of us are looking far beyond a regurgitation of historical data, and. are rightfully demanding tools that let us move beyond gut feelings and hunches. Focus On Insights, Not the Complexities of Data Management and Analytics Deriving insights from an organization s data is a circuitous process involving multiple tools and people. Getting IT to build the correct views and prepare data for analysis, asking business analysts to code reports, and finding someone to help interpret results takes more time and effort than the average person can spare. But most of us aren t in a position to write specifications or describe their requirements in ways that IT can quickly translate into usable information. The chart below, reflecting data from the Ziff Davis survey, echoes the need for an analytics platform that is easy to use, integrates simply with other information systems, and promotes collaboration. What capabilities and features would allow you to use analytics more broadly in decision making? Ease of use Simple integration with existing data stores Sharing insights with others to drive more meaningful discussions Wizards and tools to recommend analytic approaches The ability to ask plain language questions and get visual answers Ability to interact with others on analyses to quickly come to consensus Cloud-based for simple deployment and ubiquitous access Limited exposure to underlying math and computing Other 0% 10% 20% 30% 40% 50% 60% 70% 80% % Respondants ziffdavis.com 5 of 9

6 How then, can we cut out the middlemen and put insights directly into the hands of those who need them the most? And not just when IT has the resources to get the job done, but right now? You need to be able to easily tell a story visually and predict the impact of everyday decisions without help from IT and regardless of your own analytical proficiency. What if a single solution could deliver all of this via the web to you in ways that make sense intuitively and let you take action? Eliminate the Obstacle of Data Preparation People across organizations ask great questions. Can we do a better job predicting delays in deliveries for certain raw materials? Why do so many support calls about a particular product get escalated? Why do our local ad campaigns do better in some regions than in others? These are all reasonable questions but pulling together the right data to answer them can be onerous for data scientists and impossible for the rest of us. The data may need to come from systems that were never designed to be integrated or might involve individually maintained spreadsheets as well as records from enterprise information systems. Data quality can be hard to assess and most users aren t equipped to reliable join and merge tables from multiple sources. Even for dedicated analysts and data scientists, the ability to rapidly explore data, slicing and dicing with a few clicks instead of complicated queries can be a powerful accelerator. No matter who is accessing the data, preparing it for analysis and drawing the right information from the right sources is a frequent and substantial barrier to delivering insights. Addressing the Skills Gap Almost 70% of the respondents to the Ziff Davis survey noted previously described their analytics skills as either beginner or intermediate. How do you rate your analytics skills? 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Beginner Intermediate Advanced Master % Respondants ziffdavis.com 6 of 9

7 Even assuming that they have access to clean, reliable data, the lack of specific analytics skills makes basic exploratory analysis difficult. Exploratory analysis is fundamental to more sophisticated analytics. Without it, you can t know what you don t know. Taking the next step to predictive analytics is an even bigger lift. There is a reason that predictive modeling has largely been the domain of statisticians and data scientists over the years. It is both programmatically and mathematically complicated and the necessary skills aren t easily imparted with a few training sessions. Data scientists are in short supply, though (and often don t even exist outside of larger organizations); others in the organization have increasingly sophisticated analytics needs even if their analytical skill doesn t match their expertise in their line of business. Frankly, it shouldn t have to. The right solutions would allow everyone to use data to think ahead about business problems without knowing they are engaging in predictive analytics. Let the Cloud Do the Heavy Lifting Powerful analytics solutions have traditionally been both complicated and expensive to deploy. Whether implemented as desktop solutions or centralized in the data center, it is difficult to justify making analytics tools widely available when the software and infrastructure to make it work require considerable investments. As it has with so many other elements of modern business, though, cloud computing has the power to bring incredible processing power and storage capacity directly to users through their web browsers. The cloud doesn t just reduce costs or deployment complexities. It makes analytics available anytime, anywhere. Direct sales forces can access analytics on the road, improving customer targeting and directing their efforts at the deals that are most likely to close. Distributed and remote workers can have the same experience as their colleagues in the home office. Field maintenance staff can predict where problems will occur and proactively fix equipment instead of reacting to failures. This also means that smaller organizations can begin to leverage analytics just like their larger peers without significant capital expenditures. Analytics shouldn t just be for users in large enterprises; all organizations should be able to make better decisions with data. Don t Keep the Insights To Yourself Most of us operate differently than data scientists or business analysts we are already working in teams or are deeply vested in particular departments instead of working across departments or at more strategic levels in our organizations. The ability to share and collaborate around insights is critical for individuals and our colleagues. 42% of business users want to be able to interact with others on analyses to quickly come to consensus. 45% want to share insights with others to drive more meaningful discussions. -Ziff Davis End User Analytics Survey ziffdavis.com 7 of 9

8 Part of this is enabled by visual storytelling. In other cases, the solution itself needs to support collaborative approaches to analytics. In either scenario, if insights can t be made available to others inside and outside a specific line of business, then the analytics solution has much lower value to the organization as a whole and will be less likely to create meaningful change and innovation. A Closer Look At Watson Analytics Throughout this paper, we have explored important capabilities and use cases for modern approaches to analytics. Everyday analytics, in which the use of data to make decisions pervades an organization and reaches everyone, is a powerful idea whose time has come. Even though the demand for solutions that ticked off all of the boxes we ve discussed has been very high, the technology simply hasn t been available to make it all happen until now. Cognitive analytics offers a way to bridge the gap between big data and the reality of practical decision making. -Deloitte University Tech Trends 2014 Watson Analytics from IBM puts advanced capabilities directly into hands of everyone. It removes challenges of mathematical modeling and data preparation. As its name suggests, Watson Analytics is a cognitive platform that provides with multiple entry points to data and analytics projects. People will potentially approach analytics from a wide variety of learning styles, business perspectives and analytical expertise; Watson Analytics can accommodate all of them. When You Already Know What You Want If you already know what data you want to explore, Watson Analytics allows you to upload your own data, connect to existing data sources and build dashboards on the fly. It automatically assesses the quality of your data and attempts to improve data quality wherever possible. From there, you can drill down deeper into the data and move on to more advanced analytics. When You Have a Hunch If you have a hypothesis to test or a hunch to investigate, you can ask Watson Analytics a question in plain English. An IT administrator, for example, could ask which types of helpdesk tickets take the longest to resolve while an operations staffer could ask about factors that are likely to cause product failures. When You Don t Know Where to Start Because even exploratory data analysis can be overwhelming, Watson Analytics automatically look across data and suggests the most interesting starting points. Watson can detect ziffdavis.com 8 of 9

9 relationships and trends, automatically formulating potential interesting analyses or offering helpful reports, all in plain language. Conclusion Making data available to broad groups isn t especially challenging for IT departments with the desire and wherewithal. Business intelligence tools have been generating reports and dashboards and even allowing a degree of self service for some time. However, actually delivering insights to everyone when and where they need them is far more difficult. Data preparation, differing levels of analytic expertise, and complicated analytics tools have all stood in the way of users who simply need good data and intuitive platforms to let data inform practical, everyday decisions. Watson Analytics provides a complete, easy to use platform for everything from exploratory analysis to sophisticated predictive analytics, all without the need for complicated mathematics or statistical programming. Because it s delivered via the cloud, new features will be rolled out regularly and users from organizations of all sizes can begin taking advantage of this powerful platform right now. To learn more about Watson Analytics from IBM, go to ziffdavis.com 9 of 9

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