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Top 10 Best Practices in Embedded Analytics


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Top 10 Best Practices in Embedded Analytics

  1. 1. Top 10 Best Practices in embedded analytics
  2. 2. What is Embedded Analytics? Top 10 Best Practices in Embedded Analytics Recap About Logi Analytics 3 5 15 15 Table of Contents
  3. 3. 3 What is Embedded Analytics? Embedded analytics is the integration of analytic content and capabilities within business process applications (e.g., CRM, ERP, EHR/EMR) or portals (e.g., intranets or extranets). The objective is to help users work smarter by combining data and analytics to solve high-value business problems and work more efficiently, as these capabilities are available inside the applications users work with every day. to p ten best p racticies
  4. 4. 4 Dashboards and data visualizations: View charts and graphs displaying performance metrics Static and interactive reports: See tabular views of data with or without parameters and scheduling capabilities Self-service analytics and ad hoc querying: Empower users to ask their own questions by exploring a set of data to create dashboards and reports Benchmarking: Compare performance metrics against best practices from external data Mobile reporting: Ensure interactive functionality on mobile devices and take advantage of capabilities specific to mobile devices Visual workflows: Incorporate transactional capabilities directly within the analytic user interface, sometimes referred to as write-back Keep in mind, though, embedded analytics is about much more than just great- looking charts or interactive dashboards. Successful embedding requires more than simple integration at the presentation tier, but rather integration at many different levels within an application. This eBook, which highlights the top 10 best practices in embedded analytics, will provide you with the necessary knowledge to successfully implement embedded analytics in your organization. What are the most common applications of embedded analytics? to p ten best p racticies
  5. 5. 4 We also asked ISVs and SaaS providers to measure the impact embedded analytics has had on their own organizations by listing the top three ways analytics drives strategic benefits. The top three were attracting new users to their application, increasing revenue, and helping them to differentiate their product. The top three strategic benefits for IT application providers were more focused on delivering benefits as a way to improve the user experience, boost customer satisfaction, and increase user adoption. 5 to p ten best p racticies 1. Data–Driven = Value–Driven Being value-driven helps you better understand the positive impact embedded analytics has on your users, your application, and your organization. It helps you build a solid business case for your project, determine benchmarks for success, and ultimately prioritize items on your project plan. There are few different ways to look at value. We’ll explain them using findings from our State of Embedded Analytics Report, a survey of technology professionals and executives. We asked application providers to tell us the value of embedded analytics relative to the overall value of their application. Seen here as a percentage, the value of analytics has grown over time within business applications. This is very much aligned with what we see in consumer applications today. Familiar apps like Amazon, Kayak, Fitbit, and Apple iWatch are incorporating data and analytics as a core part of their offerings, which allows them to build value in and transform their products and services. We’re seeing the same transformation on the B2B side, where all modern applications are turning into analytic applications. The median value of Analytics relative to the overall application: 22.5% 2013 2014 2015 35% 43% Top 10 Best Practices in Embedded Analytics
  6. 6. 6 2. UI/UX Deserves Your Attention pay attention to user experience! Of course UI/UX is a common practice for software applications, but it hasn’t yet been fully embraced in the world of business intelligence and analytics. Beyond colors, fonts, and interactivity, UI/UX is about having a deep understanding of who your users are and how they prefer to work with data. To improve the UI/UX of analytics, you need to identify your personas and determine the experience that will help them be more productive by embedding that experience into the applications they use every day. Logi Analytics developed our Continuum of Self-Service model to facilitate this process. Regardless of where your users fall along the continuum today, or even where they move over time, you can refer to this model to match each persona to the appropriate functionality. “Consumers” “Creators” Defined Experience Query Author Share Managed Experience “Analysts” e Self-Directed Experience Information consumers prefer a defined experience where they can use the information you provide, interact with dashboards and reports, and personalize their own views of the data. More sophisticated content creators want a managed experience where they can query the data sources you’ve set up, independently author dashboards and reports, and share what they’ve created with others. True analysts need a mostly self-directed experience that’s more exploratory in nature, where they can discover new data trends and look for answers to new questions that arise. Consume Interact Personalize Connect Discover Collaborate to p ten best p racticies
  7. 7. 7 to p ten best p racticies 3. Match Capabilities to Your Users In the world of BI and analytics, there is an endless array of capabilities you can implement, but you should try to match these capabilities to what people need and want. have no fear, logi is here – Our capabilities map framework will help you match capabilities to your unique user types. The first step is to categorize capabilities into four different groups. Once this map is drawn up, you’ll match user types to those specific capabilities. In turn, this empowers you to draw up a project plan, prioritize capabilities, and plan product packaging. For an example, see the sample capabilities map on the left. Your map will look different depending on your specific requirements. Successful embedding also requires integration at four different key points in your application. When you think about embedding, consider how analytics will be integrated into each one of these capabilities within your application: Data Security User Interface Workflow UI
  8. 8. 8 4. No Data Left Behind Before you can perform analytics, you need to connect to data. As you’re building out your project, remember to think about how to connect to the data you have today as well as future data sources and types that may expand over time. Another consideration is how data from multiple sources will be displayed to users. Will you be co-presenting visualizations from multiple sources in a single view? Or do you plan to blend data from multiple sources into a single metric and visualization? Deciding on these requirements will help you define how to structure and architect your data tier. In addition, many application providers incorporate external data in their applications. They are increasing the value of their product by bringing in data to help their customers work smarter and more efficiently. One way to do this is by incorporating external industry benchmarks so users can compare their performance against their peers. ® to p ten best p racticies
  9. 9. to p ten best p racticies 5. Secure Your BI One of the first features our customers think about in embedded analytics is single sign- on authentication. After all, your application already enables users to log in for access. Even if you are bolting on a separate analytics app to your existing one, you probably don’t want to force users to log in to both applications separately. You want to create a seamless experience so your users can freely access the analytics content and capabilities they need at any time. You also want to ensure your users are seeing just the data they either a) need access to, or b) are allowed to see. Managing rights and roles, integrating those roles that may be set up already, and passing them on to the analytics application are just a few considerations to keep in mind. In many legacy and existing BI applications, you often have to synchronize profiles and continuously run a process that moves data profiles from one app to another, which can result in many complications. Look for platforms that simplify security integration without the need to separately store user profiles. Finally, consider security as it is applied to your data architecture, in particular as it relates to multi- tenancy applications. Do your customers have their data stored in individual databases or databases that co-mingle data from multiple customers? This distinction is important to implementation, and in particular how analytics will handle multi-tenancy use cases. 9
  10. 10. 1 to p ten best p racticies 6 10 6. Unite Thy UI Embedded analytics should look like your application, not someone else’s. When it comes to the user interface, white-labeling is usually a top requirement. Application providers are sensitive about ensuring the look and feel of the analytics matches their application, their company, and their brand. It’s also important to examine the embedding API and discern how easy it is for your team to embed content within your application. Take the next step and plan to implement embedding during your evaluation. Consider the larger UI/UX story and think about the types of interactivity – controls, linking, etc. – that will occur between analytic content and your existing application. Users can typically drill down into visualizations and specific records, but as they explore the data they may want to immediately go back into your application. Other times, from an input control standpoint, you may want to utilize the controls, drops downs, and filters you have already constructed in your app. to p ten best p racticies
  11. 11. 7. There’s No Flow Without “Work” Create greater value in your application by taking the final step and integrating analytics as a natural part of your overall workflow. By merging the analytic functionality with the transactional capabilities of your application, you will create a differentiated and efficient user experience. For example, Interactive Medica, a software provider to life sciences companies, created an application called a territory planner. Sales managers use this interactive interface to perform analysis on how their sales reps are performing within specific geographic territories. If managers need to reassign territories, they can do so directly within the context of this analysis. They don’t have to go to another part of the application (either a separate module or tab) to perform updates. This results in a more efficient and streamlined workflow. If you have the ability for users to update records, perform back-end processes, or even perform data write-backs, you should examine what that process is and what the development is. Part of the decision-making process is understanding how to enforce business rules in your application as well as end-user security. You may not want everyone to have the capability to update data through the analytic content you are providing. to p ten best p racticies 11
  12. 12. 12 What we’ve found is that, as you integrate analytics deeper into your application, the more you’re able to deliver on those strategic benefits to your organization and users. 8. Take a Deeper Dive into the Embedded Pool The embedded analytics maturity model describes the four ways analytics is embedded into applications based on increasing integration: data, security, UI, and workflow. Standalone – Users switch back and forth between two separate applications. Requirements include finding a way to move the data from the initial app to the analytics application. Gateway to Analytics – Users can log in to your app as well as the analytics application via a single sign-on, thus improving the user experience. Inline Analytics – Users don’t feel like they’re in a separate application, but if you actually create a reporting module, users will still see a clear separation between transactional and analytic capabilities. Infused Analytics – Analytics becomes a natural part of your application because it’s embedded within the core workflows, and oftentimes you’re building new functionality within your app. Comm ISV/SaaS Deeper integration = greater market success Deeper integration = greater value to end users Non-Comm Apps to p ten best p racticies
  13. 13. 13 9. Stretch & Tailor Your Analytics Beyond general BI requirements, you’ll probably have some unique requirements specific to your business or application. You’ll want to think about how to deliver on those requests by extending whatever analytic tools you have to provide a seamless user experience within your application. For example, SSB Consulting is a company that provides analytic applications to a wide range of diverse clients, including professional sports teams. In order to understand sales for specific seats and venues and determine pricing for events, the ability to map sales against seating maps is a critical visualization for the company. Meeting this type of need – which, for some organizations, is not planned for in advance – requires an analytic platform supporting a level of customization and extensibility that goes beyond out-of-the- box functionality. Click on the video to view the presentation and learn more about this use case. to p ten best p racticies
  14. 14. 1414 10. Be a “True” Analytics Detective In your evaluation process, you must conduct a true evaluation of your analytics provider. When it comes time to try out the software, you’ll want to: 1. Do so against your own data and data architecture 2. Embed it inside your environment, and 3. Compare it against your requirements – including requirements from your customers. This will ultimately give you a true assessment of your analytics provider and how well they will meet your needs. to p ten best p racticies
  15. 15. About Logi Analytics Logi Analytics is the leader in self-service analytics, delivering tools designed to meet the needs of users, IT, and product managers. At Logi, we are re-imagining how software can empower individuals, and the organizations and products that serve them, with analytics that can be embedded directly into the business applications people use every day. From interactive dashboards to ad hoc queries and visual analysis, Logi enables users to explore and discover insights and make data-driven decisions. More than 1,600 customers worldwide rely on Logi. The company is headquartered in McLean, Virginia, with offices in the U.K. and Europe. Logi Analytics is a privately held, venture-backed firm. For more information, visit Contact: 1-888-564-4965 15 Recap of 10 Best Practices 1. Data-Driven = Value-Driven 2. UI/UX Deserves Your Attention 3. Match Capabilities to Your Users 4. No Data Left Behind 5. Secure Your BI 6. Unite Thy UI 7. There’s No Flow Without “Work” 8. Take a Deeper Dive into the Embedded Pool 9. Stretch Tailor Your Analytics 10. Be a “True” Analytics Detective Ready to see embedded analytics in action? Sign up for a free on-demand demo here. to p ten best p racticies