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Humanizing data to create Living Services

Published in: Design


  1. 1. Data + Design Humanizing Data To Create Living Services
  2. 2. ”Nine out of 10 companies are investing in data yet the return on that investment remains elusive.”
  3. 3. Consumers, and increasingly business users, are demanding more contextualized, personalized services, but brands are challenged to deliver them. Context is key While machine learning and data science bring sophisticated models to the table, a design thinking approach can uncover many different contexts of use, delivering perfectly timed, personalized experiences to people. Personalization is expected
  4. 4. The answer is to build Living Services. We’ve already started.
  5. 5. To be living means constantly learning and changing in real time, in response to stimuli. Those stimuli include direct instructions – but also observations about people’s needs, behaviors, preferences and environment. SERVICES designed with LIVING characteristics will have the power to affect our lives in profound and positive ways – now and well into the future.
  6. 6. Living Services are created with beautiful design and powered by data, which enables the service to learn and adapt continuously. This is equally true for B2C companies as for B2B ones. This starts from five key tasks: Define your north star Understand and articulate why your Living Service exists and define exactly how you’d like to improve your customers’ lives. Write your rule book Explore how you’ll capture the information you need from your customer and understand how your service must behave so it can learn and adapt. Find triggers and micro-moments Identify the things people do, the channels they use, the places they go to, and work out what will prompt your service to react. Assemble an atomized profile Look at the detail of customers’ data and contextual information to clarify what you need to know to make their experiences delightful. Create a blueprint Map out the details of each stage, considering how each piece will fit together, who’ll be doing what, and what support will be needed within your business.
  7. 7. If services are to change in real time: Flexibility takes highest priority over silos and efficiency for its own sake. Evolution must happen at customer speed. They need to be supported by a significant operation that feeds the right data at the right time and in the right way. It’s crucial to tackle complexity head-on (touchpoints, sensors, data). It is necessary to make radical shifts in organizational culture.
  8. 8. For Living Services, we must shift from designing one experience for many, to designing many experiences for one with constantly changing needs.
  9. 9. We need a new design mindset Data is the lifeblood of Living Services. In order to create a living experience that can be continually tuned, data must be collected, analyzed and acted on from two source points: the customers and the contextual environments they find themselves in as they use the service over time. Designers must establish the capability to capture granular behavioral and customer preference data, and consider a framework of external data sources that can create a launchpad for a dynamic service. The objective is to deliver an experience that feels to the consumer as if it has correctly anticipated their intent.
  10. 10. A Data + Design approach that humanizes data …to converting insights into actions and experiences Shifts the focus from data and analysis…
  11. 11. Understand how experiences can be enhanced by data How we do it… Look both ways Understand how patterns in data can support better experiences Design Led Data Led
  12. 12. Data + Design We bring together Data Science and Service Design expertise in an integrated approach that iteratively delivers the right data insights and data-enabled services to extract value from and deliver delightful outcomes for users. U SERMODELSD ATA EXPER IEN C E R A PID PR OTOTYPIN G TEST & LEA R N IMMER SION & IN SIGH TS IN TEN SE C OLLA B OR ATION Data Scientist Approach Service Designer Approach
  13. 13. Design-led questions: • What do we wish we knew about each customer? • If we knew everything, what new services would we create? What would we anticipate? How would we flex the experience for each consumer? • How do we design to learn each user’s intent, context and attitudes? Data-led questions: • What do we know about our customers that no one else does? • What needs and changes do we anticipate? What additional data do we need to anticipate better? • How do we build millions of segments of one? Can we incorporate new data sources? We ask…
  14. 14. A Data + Design approach to Living Services Design For Data Apply data layers to every design artifact. Define how sensing, reaction, feedback and evolution is designed into your service. Design With Data Augment qualitative research with quantitative analysis to gain a more holistic understanding of our users. Aim to create dynamic digital footprints. Design By Data Using data as a raw material in our creative process. Sketch with code and use generative technologies in our experiments.
  15. 15. Understand We blend digital footprints with quantitative and qualitative research to get a more holistic understanding of our users.​ Get We leverage transactional level data stored in our clients' databases, publicly-available data, or data that we capture in research. ​ Apply Designing with data is about overlaying concepts and designs with data that is available, either internally or externally. Design With Data
  16. 16. Design For Data Plan As we build roadmaps for products and services, we build in instrumentation so data collections are an integral part of product and service strategies. Collect We can design how we collect data, such as, with sensors either physically or digitally, and plan data sharing partnerships. Profile Designing for data also sets up the analytics to refine the value of the underlying data. We use tools like the customer genome and contextual awareness to bring multiple data sets together to create an understanding of our customers and their context.
  17. 17. Design By Data Personalize The atomized Profile is the ever- changing dynamic profile of your customers’ preferences, context, history, needs and wants. It contains data that is relevant to your customers as well as the environment around them. It’s based on historical interaction data and the instrumentation of services. Contextualize It’s important to remember that this is not just about screens, It is about delivering the right experience in the right way, whether that be via a screen, a chatbot, or a personal assistant. Automate Designing by data is about delivering true Living Services. When we understand the individuals we are building experiences for, and the context they are in, then we can build dynamic experiences that adapt to changing needs enabled by technology such as AI.
  18. 18. Data + Design answers the following: I have created the data platform. How can I get my organization to adopt and use the data insights I provide to make better decisions? Personalization is important. How can I enhance my existing products and services using data to create better experiences for my customers? Artificial Intelligence. How can I use it to create new services that anticipate customer needs?
  19. 19. Worldwide Telco (WWT) C A SE STU D Y B R IEF How can WWT increase data consumption? Fjord and Accenture Analytics co-developed an interactive story based around 3D visualizations and decision-assistance tools showcasing: The project crystalized the role of the Chief Analytics Officer and Data Science team to the Executive Committee. • Which customer through • Which apps on • Which device • When to contact them • Where to push the notifications A PPR OA C H IMPA C T
  20. 20. Global Beverage Producer How can GBP identify and address brand specific loyalty deterioration? Fjord and Accenture Tech Labs leveraged a cross- disciplinary team to design and develop a mobile analytics experience which: The prototype distilled a clear decision-making process that enabled direct and efficient diagnosis of performance issues. This project therefore illustrated the power and benefit of a well-design data analysis experience. • Revealed acute issues with brand performance • Enabled analysis by focusing on relevant data • Unlocked insights by researching analysts’ needs C A SE STU D Y B R IEF A PPR OA C H IMPA C T
  21. 21. The Customer Genome in Action How can a large coffee chain increase share of customer wallet in a saturated market? C A SE STU D Y B R IEF The example shown on the next page was motivated by a real analysis of client data, where Accenture Technology Labs, provided with 2TB of transaction data, illustrated the capabilities of the Customer Genome in a two-week sprint. The customer’s behavior changes — they now shop in hot and cold weather, producing additional revenue. A PPR OA C H IMPA C T
  22. 22. The Customer Genome in Action
  23. 23. Thank you