Moving from data to insights: How to effectively drive business decisions & gain competitive advantage
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Firms have become obsessed with data. But the key to competitive advantage is not just more or bigger data or big data technology, it is finding actionable insights from all the data as well as embedding insight in processes and applications. This requires a change in your approach - modernized architecture and embedding insights and data in you business decisions It also requires a change in how your people work systematically to find, test and implement insights. In this webinar, Forrester Vice President and Principal Analyst Brian Hopkins will present results from two years of research into these ideas and recommend to attendees how they can get the most out of their data and analytics to drive effective business decisions and gain competitive advantage.
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Moving from data to insights: How to effectively drive business decisions & gain competitive advantage
- 2. It’s Time To Rethink Big Data Brian Hopkins, Vice President, Principal Analyst June 2016 @practicingea #InsightsDriven, #SystemsOfInsight
- 3. © 2016 Forrester Research, Inc. Reproduction Prohibited 3 All possible data All possible actions Most firms don’t consistently turn data into action Source: Forrester’s Global Business Technographics® Data And Analytics Survey, 2015 73% 29% of firms aspire to be data-driven. of firms are good at turning data into action.
- 4. © 2016 Forrester Research, Inc. Reproduction Prohibited 4 All possible data All possible actions Most firms don’t consistently turn data into action Source: Forrester’s Global Business Technographics® Data And Analytics Survey, 2015
- 5. © 2016 Forrester Research, Inc. Reproduction Prohibited 5 You are used to “football”-style analytics Pregame strategy
- 6. © 2016 Forrester Research, Inc. Reproduction Prohibited 6 You are used to “football”-style analytics Pregame strategy Tactical execution Call play Execute Regroup Evaluate
- 7. © 2016 Forrester Research, Inc. Reproduction Prohibited 7 You need to rethink big data analytics.
- 8. 8© 2016 Forrester Research, Inc. Reproduction Prohibited An insights-driven business harnesses insights to consistently turn data into effective action.
- 9. 9© 2016 Forrester Research, Inc. Reproduction Prohibited What are insights-driven businesses doing that’s so unique?
- 10. © 2016 Forrester Research, Inc. Reproduction Prohibited 10 They are customer-obsessed Systems of engagement touch people Systems of automation and IoT connect the physical world Systems of record host processes Systems of insight power digital business Source: Digital Insights Are The New Currency Of Business Forrester report
- 11. © 2016 Forrester Research, Inc. Reproduction Prohibited 11 They are customer-obsessed Systems of engagement touch people Systems of automation and IoT connect the physical world Systems of record host processes Systems of insight power digital business Source: Digital Insights Are The New Currency Of Business Forrester report
- 12. © 2016 Forrester Research, Inc. Reproduction Prohibited 12 They instrument and measure everything Applications DecisionsProcesses
- 13. © 2016 Forrester Research, Inc. Reproduction Prohibited 13 They build systems of insight All data Possible actions Insights team Digital insights architecture Right data Effective actions Source: Digital Insights Are The New Currency Of Business Forrester report
- 14. © 2016 Forrester Research, Inc. Reproduction Prohibited 14 They build systems of insight All data Possible actions Insights team Digital insights architecture Right data Effective actions Source: Digital Insights Are The New Currency Of Business Forrester report
- 15. © 2016 Forrester Research, Inc. Reproduction Prohibited 15 They build systems of insight All data Possible actions Insights-to-execution process Insights team Digital insights architecture Right data Effective actions Source: Digital Insights Are The New Currency Of Business Forrester report
- 16. 16© 2016 Forrester Research, Inc. Reproduction Prohibited A system of insight is the business discipline and technology to harness insights and consistently turn data into action.
- 17. © 2015 Forrester Research, Inc. Reproduction Prohibited 17 Tesla’s driving experience is powered by insight Pipeline Insights services Engineers Firmware developers Data scientists Data engineers
- 18. © 2016 Forrester Research, Inc. Reproduction Prohibited 18 Source: Digital Insights Are The New Currency Of Business Forrester report You will have many systems of insight
- 19. © 2016 Forrester Research, Inc. Reproduction Prohibited 19 Business leader Manages the team to optimize a specific business outcome Technology leader Responsible for insights testing, implementation, and architecture Domain experts Recognize insights worth the investment Developers Test and implement insights in software and business rules Data scientists Build models and exercise them to reveal potential insights Data engineers Gather, assess, integrate, prepare, and manage data Insights teams are agile and collaborative Source: Digital Insights Are The New Currency Of Business Forrester report
- 20. 20© 2016 Forrester Research, Inc. Reproduction Prohibited
- 21. © 2016 Forrester Research, Inc. Reproduction Prohibited 21 Pattern: Use digital behavior to anticipate needs Problem • Processing a customer’s digital fingerprints is time- consuming. • Results in batch updates to predictive models. • Content is not customized in real time
- 22. © 2016 Forrester Research, Inc. Reproduction Prohibited 22 Building blocks • Mobile/web application • Algorithm engines • Insight execution code; APIs • Data science tools • Digital channel data pipeline Insights execution Experiences change based on real-time behavior. Problem Key people Developers and analysts • Processing a customer’s digital fingerprints is time- consuming. • Results in batch updates to predictive models. • Content is not customized in real time Pattern: Use digital behavior to anticipate needs
- 23. © 2016 Forrester Research, Inc. Reproduction Prohibited 23 Building blocks • Mobile/web application • Algorithm engines • Insight execution code; APIs • Data science tools • Digital channel data pipeline Insights execution Experiences change based on real-time behavior. Problem OutcomesKey people Developers and analysts • Processing a customer’s digital fingerprints is time- consuming. • Results in batch updates to predictive models. • Content is not customized in real time • Increase uptake of marketing offers • Increase cross-sell and upsell • Higher customer loyalty • Reduced channel friction Solutions • Personalized search recommendations • Guided navigation • UI personalization • Automated Q&A • Troubleshooting guides • Call center routing • Sales support Pattern: Use digital behavior to anticipate needs
- 24. © 2016 Forrester Research, Inc. Reproduction Prohibited 24 Building blocks • Hbase • Solr • Node.js • Lilly Indexer • Rabbit messaging Insights execution New web search terms queued and fed to a clustering algorithm. server. Problem Key people Data scientists developed an auto-clustering algorithm.Art.com was missing sales opportunities daily because it wasn’t connecting users with other related products when they searched the website. Outcomes Results include increased cross-sell, automatically creating new search clusters of related items, and lower drop- off points. Solutions A custom auto-clustering pipeline algorithmically creates new groups of related art as new search terms are seen. Example: Art.com implements semantic search
- 25. © 2016 Forrester Research, Inc. Reproduction Prohibited 25 Art.com’s system of insight › Notice the loop. › Knowledge built over time › Implementation took an insights team. › Real-time architecture New keyword? Text analytics Similarity algorithm Create art cluster Store for future
- 26. © 2016 Forrester Research, Inc. Reproduction Prohibited 26 Food for thought › It’s about customer engagement in real time. › It’s about optimizing experiences in closed loops (not big data). › It’s a team sport – data scientists, developers, business experts. › It takes a new architecture. › It takes learning (and that means training).
- 27. forrester.com Thank you Brian Hopkins Twitter: @practicingea Forrester reports: Digital Insights Are The New Currency of Business Transform Customer Experiences With Systems Of Insight Brief: Why Data Driven Aspirations Fail Upcoming: The Insights-Driven Business Upcoming: Insights Service Providers
- 28. 28© Cloudera, Inc. All rights reserved. Rahul Deshmukh | Director, Solutions & Industry Marketing Big Value with Big Data
- 29. 29© Cloudera, Inc. All rights reserved. Our relationship with data is changing
- 30. 30© Cloudera, Inc. All rights reserved. With this Data comes Opportunities and Risks
- 31. 31© Cloudera, Inc. All rights reserved. Data and Insights are Transforming Business DRIVE CUSTOMER INSIGHTS IMPROVE PRODUCT & SERVICES EFFICIENCY LOWER BUSINESS RISK MODERNIZE ARCHITECTURE
- 32. 32© Cloudera, Inc. All rights reserved. OPERATIONS DATA MANAGEMENT BATCH REAL-TIME PROCESS, ANALYZE, SERVE UNIFIED SERVICES RESOURCE MANAGEMENT SECURITY FILESYSTEM RELATIONAL NoSQL STORE INTEGRATE BATCH STREAM SQL SEARCH SDK Cloudera Enterprise Making Hadoop Fast, Easy, and Secure for the Modernized Architecture Hadoop is a new kind of data platform. • One place for unlimited data • Unified data access Cloudera makes it: • Fast for business • Easy to manage • Secure without compromise
- 33. 33© Cloudera, Inc. All rights reserved - Confidential • New insights into customer behavior, abandoned online shopping cart behavior with unified customer data • Marketing spend optimization through channel attribution analysis • Improve supply chain and reduce inventory costs • Improved ability to predict returns DRIVE CUSTOMER INSIGHTS
- 34. 34© Cloudera, Inc. All rights reserved. • End-to-end view of data is helping save lives by detecting sepsis early enough for successful treatment • Has saved 100s of lives already & reduced hospital readmissions • Centralized data from many systems available in a secure environment • 2PB+ in multi-tenant environment supporting 100s of clients IMPROVE PRODUCTS & SERVICES EFFICIENCY
- 35. 35© Cloudera, Inc. All rights reserved. • Deeper analytics from customer profile data • 50% increase in customer retention while 2x increase in policies issued • Ability to analyze 10s of millions of quotes in under a minute • $5 million claim cost reduction through fraud prevention DRIVE CUSTOMER INSIGHTS
- 36. 36© Cloudera, Inc. All rights reserved. • Comprehensive view of risk for 80 years of historical data across all 50 US states with EDH • Faster data preparation and ETL using Cloudera with Spark • Created highly refined pricing models • Reduced speed to create pricing models by 75x resulting in timely and customized offers to customers LOWER BUSINESS RISK
- 37. 37© Cloudera, Inc. All rights reserved. Getting Started is Easy ① ② Download or Deploy in the Cloud Signup for Training Contact us or a Partner to Start a POC ③
- 38. 38© Cloudera, Inc. All rights reserved. Thank you
Editor's Notes
- Ted & Brian – Brian starts off 73%, but, Ted takes back half 29%
- Ted & Brian – Brian starts off 73%, but, Ted takes back half 29%
- Moved these here, think its more appropriate, felt odd in the back half. Ted you want to do this one – its about traditional analytics, slow, methodical, you have time to regroup replan, etc.
- Moved these here, think its more appropriate, felt odd in the back half. Ted you want to do this one – its about traditional analytics, slow, methodical, you have time to regroup replan, etc.
- Image source: TorrentsGame.org (torrentsgames.org/pc/fifa-street-3-pc.html) Brian does this one – I have a voice over in my head.
- Ted
- Brian
- Ted – It will help your team get it if we put systems of insight in a bit of context. You have heard us talk about systems of engagement (click). They touch people, need to keep up with them and offer a ton of data you might be able to use to engage. Systems of record on the other hand….. But to engage customers you frequently need SoR data too, mobile and social aren’t enough. Brian – Finally, we have defined systems of automation as the way we will connect with control and automate the physical world (click) But we found that the insights needed engage customers that use physical world products, often came from all three systems (click) Systems of insight fit between all these things ensure that that data each systems is producing can be used for creating insight and action in the other systems – powering digital business.
- Ted – It will help your team get it if we put systems of insight in a bit of context. You have heard us talk about systems of engagement (click). They touch people, need to keep up with them and offer a ton of data you might be able to use to engage. Systems of record on the other hand….. But to engage customers you frequently need SoR data too, mobile and social aren’t enough. Brian – Finally, we have defined systems of automation as the way we will connect with control and automate the physical world (click) But we found that the insights needed engage customers that use physical world products, often came from all three systems (click) Systems of insight fit between all these things ensure that that data each systems is producing can be used for creating insight and action in the other systems – powering digital business.
- Ted – this is a graphical rep of the previous slide. You can choose which one you want, was just trying to make the slides a bit sexier.
- Ted So how do you build a system of insight – and you will have many of them? It’s a [click] new operating model that blends people, process, and technology working together. The first element is a new team we call an [click] insights team that blends technical, business, and data skills on an agile team. These teams work in a new way [click] that we call an insights-to-execution process. We’ll explain this process in more detail in a moment. But remember that it’s more than a
- Ted So how do you build a system of insight – and you will have many of them? It’s a [click] new operating model that blends people, process, and technology working together. The first element is a new team we call an [click] insights team that blends technical, business, and data skills on an agile team. These teams work in a new way [click] that we call an insights-to-execution process. We’ll explain this process in more detail in a moment. But remember that it’s more than a
- Ted So how do you build a system of insight – and you will have many of them? It’s a [click] new operating model that blends people, process, and technology working together. The first element is a new team we call an [click] insights team that blends technical, business, and data skills on an agile team. These teams work in a new way [click] that we call an insights-to-execution process. We’ll explain this process in more detail in a moment. But remember that it’s more than a
- Brian
- Telsa has made a big investmen in instrumenting its product and using all of that data to create a differentiating customer experience. Like I said previously, Telsa realizes that all the data it needs cannot be stored in one place, so it has a pipeline that loads it into a bunch of differnt data store (click). They have a federated set of teams, that work together to spot problesm with their cars and fix them before they happen (click) that's the Tesla experience (click) Here is how is works - data scientist work with engineers to develop scripts that lets the engineers run parameterized scripts on demand, these look at fresh car performance data (click) When they spot a problem, they identify potential fixes to Firmware developers who often can deploy solutions over the air (click). For example in one case they spoted ann issue that could benefit from additional performance and did a live over the air firmware update that upped a models horsepower!. when I asked Tesla why the do this, its all about the experience.
- Ted
- Ted
- Brian – On behalf of Ted and I, I’d like to thank you for sharing this time with us and let us share this exciting research with you. Our wish for you is that you see in this some of the things you are already doing or aspiring to, and also see some new ideas (insights) that lead to action tomorrow as you seeek to deliver on the benefits your firm expects from data and analytics. I see there have been a few questions typed in as we went, so let’s get to those.
- What once was a cost to be managed is now a source of competitive advantage and new revenue streams. Organizations are actively working to gather more data by instrumenting applications, platforms, and physical devices to create more of it and storing it for a longer time horizon– in order to drive this advantage. Data is now a strategic asset, and you need a strategy for it.
- Opportunities that help you generate revenue, acquire new customers, retain customer. Data used wisely can provide competitive advantage to organization. Ignoring the opportunity can risk your business growth with lost market share and reduced revenue.
- Apache Hadoop is, in many ways, enabling this shift. With maturity of the platform and technology ecosystem, and with better understanding of the Hadoop ecosystem, the conversation has shifted from technology and pure cost savings, to driving business value with data. Organizations want to discuss aligning data to business objectives in order to derive even greater value. The three areas of opportunities within businesses generally are: Customer and Channel – How do I build a 360 picture of my customer to deliver new revenue streams? Data-Driven Products – How can I build better data-driven products and services, at lower cost? Security, Risk, and Compliance – How do meet compliance regulations and preserve data security to minimize our corporate risk profile?
- Every Hadoop platform lets you store unlimited data, and access it in a variety of ways. At Cloudera, we make Hadoop fast, easy, and secure so you can focus on business results and less on the technology. An enterprise data hub can store unlimited data, cost-effectively and reliably, for as long as you need, and lets users access that data in a variety of ways. Data can be collected, stored, processed, explored, modeled, and served in one unified platform. It’s connected to the systems you already rely on. Cloudera Focuses on making Hadoop fast, easy, and secure Cloudera’s enterprise data hub, is differentiated in several crucial areas. We provide: Leading query performance. The enterprise management and governance that you require of all of your mission-critical infrastructure. Comprehensive, transparent, compliance-ready security at the core. An open source platform that is also built of open standards – projects that are supported by multiple vendors to ensure sustainability, portability, and compatibility. Our platform runs in your choice of environment, whether on-premises or in the cloud. Cheat Sheet version: Our enterprise data hub is: One place for unlimited data Accessible to anyone Connected to the systems you already depend on Secure, governed, managed & compliant Built on open source and open standards Deployed however you want Coupled with the support and enablement you need to succeed.
- Company Background: M&S is an UK based multi-channel retailer that has around 850 UK stores, 480 international stores in 54 territories. The company sells stylish, high value clothing and home products, as well as outstanding quality food. Problem: M&S was struggling to understand customer behavior and why customer abandoned shopping carts. Additionally, there were limited insights into supply chain efficiency as well understanding what marketing channel was most efficient. For a large organization like M&S, any item that is returned leads to revenue loss – there was no easy way to predict returns. Solution: M&S integrated many different data sources into a single platform (click streams, in-store POS, online ordering, and social media) Value: Used big data analytics to develop a 360-degree customer view offering better understanding of purchase patterns and shopping behaviors across channels with an end goal to design the perfect customer experience. M&S was able to: Drive revenue from better understanding of customer behavior Optimize marketing spend Improve supply chain and reduce inventory costs Predict product returns
- Company Background: Cerner is a technology company committed to the systemic improvement of healthcare. Challenge: Cerner historically focused on electronic medical records (EMR) but has expanded to help across the spectrum of health and care information. Healthcare data is fragmented and incomplete; in almost all cases no one can see an end-to-end view of a person's health data. Solution: Hadoop is being used to bring together data from multiple disparate sources to synthesize that end-to-end view. Value: The end of end view of data is helping Cerner save lives through early detection of Sepsis. They have already saved 100s of lives and reduced hospital readmissions. Patient privacy is very important and Cerner’s 2PB+ environment is secured through robust and centralized security.
- Company Background: A UK insurance holdings underwriter that provides insurance solutions to over 1,750,000 customers Problem: Unable to provide personalized pricing due to limited customer insights and delay in creating quotes. Lack of deeper analytics on customer profile data. Value & Solution: Markerstudy uses a Cloudera-based enterprise data hub to use real-time and existing customer data for a more accurate overview, ensuring that it provides the most appropriate insurance product and price. Reduce fraud and lower/tailor pricing as a competitive advantage. The new platform allows the to add new 3rd party data sources such as weather and financial market data.
- Background: Allstate is one of the largest personal insurance companies in the US Challenge: Because of all the data Allstate has collected over the years -- both internal, and from external feeds such as traffic patterns, weather data, etc. -- they were unable to analyze everything at scale. For instance, they could look at a single state at a time -- and each state’s analysis took about a day -- but could never run analytics on all 50 states at once. They’d never been able to do large scale graph link analysis. Solution: Allstate has built a data lake using Enterprise Data Hub which spans every system in the company to break down data silos and provide a single, comprehensive view of all their data. Value: Allstate can analyze 80 years’ historical data on all 50 US states at once for a comprehensive view of risk, instead of looking at one state at a time. 2) Created highly refined pricing models 3) Faster time to value and 75x improvement in pricing models for customized offers ** Backup reading Data sources that feed into Cloudera include telematic sensors, customer data, public data, economic data, and Allstate’s EDW. Some of these data sources have never been brought together before, and much of the historical data which hasn’t been digitized couldn’t be analyzed in tandem with external sources until now. The universal data archive is integrated with their incumbent mainframes and data warehouses -- they’ve designed their Cloudera system to complement, not replace, existing infrastructure. * Backup reading Hadoop components in use include Hive, Pig, and Python over Hadoop Streaming. Allstate uses Cloudera Manager to manage their Hadoop clusters. Benefits: Allstate is better equipped with their universal data archive to look back into more historical data than they could before, which helps them build out more accurate and detailed predictive models. With the deeper, more holistic view offered by Allstate’s universal data archive, they can do things like: Create better and more customized offers for customers; Develop more precisely tuned pricing models; and Get a better view of risk at the individual customer level. Data preparation and ETL run much faster on Cloudera, which means Allstate can finally bring together data from all 50 states for analysis in 16 hours, whereas it took a full day for each state separately before. That’s about a 75X speed-up using Hive, so it would be even faster on Impala. What would have taken a month or two of just running reports was finished in one day with Cloudera. Also, the Cloudera system has brought a social and cultural change to Allstate. Employees across the organization can now share their data and work together to build better descriptive and prescriptive analytics.
- When we think of business risks, there are many areas that affect business risks. Some of the key areas are cybersecurity, fraud and compliance. Identifying cybersecurity risk, preventing fraud and meeting compliance requirements help mitigate risks within the organization. Let’s dive into one of the key areas that affect business risk - Cybersecurity
- Thank you very much for your time and attention!!