Big Data - Taming the Data Monster


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We are seeing an exponential growth in the scale, scope and immediacy of data, but how can companies commercialise this data? In this presentation we'll look at four ways companies can make the most of the data they have.
1. Turn data 'exhaust' into new revenues
2. Diversify your data to unlock value
3. Join the intention economy
4. Be an artist and a scientist.

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  • As we’ve looked at this area more closely, we’ve found some stuff that we think is pretty interesting, and in fact four big things captured our imagination.There’s a wholesale shift in consumer behaviour, happening at the same time as a wholesale shift in marketers behaviour. The companies with the biggest right to play are actually those who will find it most difficult to winConsumers, agitated by governments are becoming more aware of their rights and their valueAnd transformation in technology means many companies will be left behindIt turns out that everything is still to play for..
  • We’ve seen a quantum leap in both supply-of, and demand for real-time, personal data.Independently, but in parallel, consumers and marketers have come to realise (enabled by technology) just how useful data can be in making life easier, more interesting, more convenient. The shift to quantified self – whether in fitness & wearable devices, location-based networks or lifelogging are building a really detailed, contextual graph of consumer purchases, preferences and behaviours.Marketers meanwhile are looking to apply great targeting horsepower to radically improve the timing, message and channel of delivery of marketing messages. In the move away from one-size fits all, data promises to make 1:1 relevent marketing a reality. That’s why there is a bun-fight to give away free services, content, whatever. Remember, if you’re not paying for it, then you’re probably the product.
  • At first glance, big businesses have the winning ticket here.They have millions of customersThey have massive archives and backbook of dataThey are recognised and establish brandsThey’re inheriting the keys to the data kingdom – energy companies are the recipients of new smart data, banks the receipients of new transactional data, telecoms commpanies the recipients of new location data.They can’t lose, right?It’s not quite that simple. The very assets that position incumbent brands and playesr so strongly have the potential to undermine them. Few consumer brands have a right to step into the ‘big brother’ role unchallenged. Toxic bank or energyCo brands will find it especially troubingThose millions of customers will be vocal and problematic when you try to monetise them. Especially if you can’t get the basics of your core service right (ask the banks that recently changed T’s and C’s to allow them to package up and sell data).The largest companies are the ones facing the brunt of legislative oversight – data compliance will disempower them from the off, and cause them to be massively conservative for fear of the wrath of the data regulatorNew, agile players have everything to win. No legacy to worry about, no customers to offend – just fresh, agile approaches and aspirational customer-friendly brands focused on making life easier and more fun. Big businesses have everything to win and everything to lose.
  • Inspired by media agitators and new regulation, consumers are becoming more savvy about their data footprint, and the inherent value in their data. The shift in power which will see consumers taking back ownership of their data, and provision of new tools to monetise it heralds a new marketing dynamic. Consumers are waking up to the value and importance of data about themselves – and are increasingly reluctant to give it away for free.Or are they? Annika will talk you through an interesting case, which suggests that customers may be taking greater risks with their data at the same time as the start to understand its value.. (roboform video. 28m users giving most intimate passwords etc – website doesn’t even list responsible officers, and they won’t answer the phone if you call them up..)
  • Big data creates some very practical technology issues for big businesses. Their infrastructure was designed for a different world – and simply isn’t scaled for the big data world.A noddy example: (Question to audience) How many people have a limit on the size of incoming and outgoing files? Many of our clients have a 5mb limit on emails. In an age of multimedia it feels archaic – but in the age of big data, it reflects creaking infrastructure that risks not being fit for purpose.Let me give you another example. One of our clients – a very progressive and future focused FS provider is at the forefront of the digital commerce economy. It has email addresses for less than 50% of its customers, and no clear way of capturing them. It has mobile phone numbers for only 30%.Over 85% of IT spend in Financial Services and Energy companies across Europe is driven by compliance and regulatory burden. No surprise then that Big Data projects usually happen on the side of core infrastrcuture, rather than heralding it’s re-creation. This inherent lack of integration of the new and old is worrying.Add to this a growing skills shortage – and the very real risk that the brightest and best data analysts, entrepreneurs and engineers will choose to work for ‘next generation’ businesses rather than slumbering giants – and it’s easy to paint a picture in which many big businesses not only struggle to surf the big data wave, but in fact get drowned by it.
  • So, 4 things captured our imagination:There’s a wholesale shift in consumer behaviour, happening at the same time as a wholesale shift in marketers behaviour. The companies with the biggest right to play are actually those who will find it most difficult to winConsumers, agitated by governments are becoming more aware of their rights and their valueAnd transformation in technology means many companies will be left behindIn light of this, how on earth do big companies, and in particular those individuals within them searching for revenue growth, pursue their big data agenda?
  • We’ve had the great privilege to try and answer this question with clients across multiple sectors – energy, transportation, financial services, public sector and beyond. We’ve developed some perspectives on how to do this effectively – and I’m going to quickly share 4 of the ‘no regrets’ recommendations that we’ve developed.
  • Talk to the slide
  • Annika video
  • annika
  • Don’t settle for todays world view. If you want to avoid being reinvented by data, you need to be beuilding a bigger, broader perspective on your customer, market and business modelTalk to the slide
  • Annika video
  • annika
  • The most obvious no-regrets step towards big data is to build a more participative engagement with your customers.Big data is not just MORE data – it’s more effective data. Customer generated content – whether tracking, preference or intention enables service providers to compete effectively as the pendulum shifts from brand push to consumer pull.And don’t forget communities of interest are buyers and consumers every bit as much as individuals.Talk to the slide
  • Annika + Video
  • Annika
  • One of the biggest risks in big data, is that you only find what you’re looking for. A team of left-brainuber-analysts get model spectacular algorithms and distill deeply granular insight into a known world. But only right-brain, creative thinking will identify new paradigms, challenge the status quo and truly find new signals in the noise of big data. Even more, creative expression through visualisation and storytelling are the key to creating emotional connection with an audience – even the most rational business audience. Storytelling is the soul of data and visualisation is it’s spirit. Who’d have thought? Unlocking value in data, not just through analysis and technology, but artistry and creative endeavour.
  • Annika
  • Annika
  • Questions.Lead over to the fact that when it comes to creating value from data and engaging people with its results, we should try to be artist … and create magic …  cool intel app
  • Big Data - Taming the Data Monster

    1. 1. Big Data | Taming the Data Monster Insight Briefing Market Gravity
    2. 2. BigData31 We are seeing exponential growth in the scale, scope and immediacy of data What is ‘Big Data’? As intended, the term „big data‟ refers to datasets which are so large and complex that they overwhelm standard software and hardware, requiring new technologies and approaches. Regardless of the tools that are used to manipulate data, three driving forces are bringing major change and opportunity. More data The rise of mobile and increase in internet usage globally is driving huge growth in data volumes generated From a wider range of sources Smart devices and the popularity of social media is creating new (often unstructured) information sources Available faster than ever before Advances in technology and processing power and enabling data-driven insights and decision making, in real-time Global Data Volumes Generated 2005: 130 Exabytes 2010: 1,227 Exabytes 2015 Forecast: 7,910 Exabytes Source: IDC, EMC
    3. 3. Implications31 So, for those of us in the growth business, is there more to big data than hype? 4 things have captured our imagination The Data Explosion Everything to win, everything to lose Drowned by legacy?A shift in power
    4. 4. Quantified self is exploding the supply- side of available data Life-logging has become a mainstream activity, integrating multiple devices and channels • Tracking location, activity, behaviours • Capturing data, metadata & audio/video footage Demand-side shift to data-driven digital marketing Digital channels will continue to grow and seamless cross-channel experiences will become the norm • Increase in sophistication of digital marketing, e.g. measurability of social media campaigns • Data spend focused on driving relevance – in time, location and personalisation New players and channels Companies are providing „free‟ services in order to capture data they can monetise elsewhere. • “If you‟re not paying for it, then you‟re the product” Implications32 New technologies are enabling new data-driven competition for purchases Insight 1: The Perfect Data Storm
    5. 5. Big companies with the most to gain from data are also often the least trusted Consumer trust is at an all-time low Consumer backlash across multiple industries has impacted many major reputations and brands • Banking: financial crisis / product mis-selling • Energy: price rises / high profits • Telco: excessive charges Many brands don’t have license to innovate Brands may not stretch to new services, particularly in businesses that are perceived as „utilities‟ • Consumers more interested in „fixing the basics‟ • Hard to divorce new services from frustrations with existing New players have an advantage Disruptive start-ups are more nimble, able to take more risks and act on data insights quickly • Less at stake – financially and operationally • Less long-term brand equity Implication 2: Questionable rights to play Implications32
    6. 6. Increasing awareness of the value in data Consumers recognise what their personal data is worth and expert value in return for providing it • 2/5 of consumers see their personal data as an asset, tradable for better prices and offers1 New tools that empower consumers New „personal data store‟ services are emerging that allow consumers to manage and sell their data • UK market projected to be worth £1BN b 20162 More protective regulation Data protection regulation continues to evolve, placing further obligations on businesses • Updated EU regulation expected 2014-16, providing better coverage of social networks and increasing corporate fines for breaches Implications32 Consumers are empowered to have high expectations of how their data is used Implication 3: Need to show real consumer value Source: 1) Direct Marketing Foundation / Future Foundation, 2012; 2) Ctrl-Shift / Information Age, 2012
    7. 7. There‟s a mounting tidal wave of data – it‟s hard enough just to stay afloat Winners will derive actionable data insights Technological capability and analytical skills alone aren‟t enough to use data for commercial gain • Organisational structures and processes need to enable rapid, data-driven decision making But talent shortages add to the challenge… The need for specialist skills will increase, with high competition for the best people • By 2018, US will be short 190k people with the required analytical skills and 1.5m managers and analysts to analyse big data and make decisions …and current IT investment levels aren’t enough to stand still Despite continued growth in corporate IT spend, data volume growth will likely outstrip capacity • 40% projected growth in global data generated Implication 4: Potential for analysis paralysis Implications32
    8. 8. Why should we care? Because effective use of data is now a critical competitive advantage The challenge Implications32
    9. 9. So, how should the big companies respond?
    10. 10. InitialInsights5 Based on our work with clients across multiple industries, we believe there are four possible responses to the challenge Turn data „exhaust‟ into new revenues New insight services derived from existing data • Hidden value in data produced as a by- product of the core business • Moving beyond existing customers • Added value through insight and advice Be an artist - and a scientist Complimentary skills to realise data potential • Statistical analysis needs to be robust… • …but only a „human‟ perspective can understand the real drivers for conclusions • Creative communication wins over audiences Diversify your data to unlock value Combining datasets with new partners • New connections and patterns • Deeper relationships with existing customers • Increased relevance to new customers 10 Thoughts on the future: 4 ways to respond to the challenge Join the intention economy Embrace the tools of the empowered customer • Customers express intentions directly to sellers • Shift from CRM to Vendor RM • Focus on small data, not big data InitialInsights33
    11. 11. Turn data exhaust into new revenues “Google decided to keep all the information from users' spelling mistakes in their search engine, data that most people would throw away. They looked at what people typed, even if they spelt Ferrari with eight 'r's. Now you can make typos in Google and still get to where you want to go. They've effectively developed the world's most powerful spellchecker.” Mark Whitehorn, Chair of Analytics, University of Dundee Be careful what you throw away There may be hidden value in data produced as a by-product of your daily core business activities Moving beyond your existing customers You may not yet have close relationships with those willing to pay for your data Added value through insight and advice Raw data alone will rarely carry much value – but the combination of data with experience and insight will SellDataExhaust3
    12. 12. Turn data exhaust into new revenues Case Study: Smart Steps from Telefonica & GFK | Deriving consumer insights from mobile phone location data SellDataExhaust3 Smart Steps uses mobile phone location data to offer retailers, councils and public safety bodies information about foot-fall in different locations. Socio-demographic insights Segment footfall in specific locations using socio-demographic criteria, measuring actual behaviour rather than perceived or claimed behaviour Existing customer base insights Information on when your customers are there and how often. Tells you if the crowd stayed at home, or went elsewhere. Also tells you if your competitors‟ areas experienced the same thing. Campaign management Enables retailers to measure marketing campaign success against naturally growing or declining footfall around their stores
    13. 13. Turn data exhaust into new revenues How can big companies harness the opportunity? 1. Co-create with new customers Work with a range of potential customers when exploring the opportunity to help uncover unmet needs and new ideas for harnessing data exhaust to gain insight and solve problems 2. Involve technical teams early Don‟t be afraid of involving the realists early on - bringing technology and analytical experts into the ideation process will not only result in more feasible ideas, but also bring new perspectives 3. Consider a range of options to deliver required capabilities Offering client value from new services will usually require a combination of data and consultative service to deliver tailored insights and recommendations – consider buy, build and partner routes to deliver this capability SellDataExhaust3
    14. 14. Diversify your data to unlock value “Making official data public could spur lots of innovation. In Europe the information held by governments could be used to generate an estimated €140 billion ($180 billion) a year.” The Economist, 2013 New connections and patterns Gain a broader view of trends and drivers by combining your internal datasets with those from outside – businesses, governments and consumers Deeper relationships with existing customers Move from a silo view of what your customers buy and how they behave within your business to a fuller picture of their lives and needs Increased relevance to new customers Combine data with those of partners to create insight services for new customers that need to understand relationships between divergent industries, customers and environmental factors DiversifyData3
    15. 15. Diversify your data to unlock value Case Study: Zest Finance | Big Data Underwriting ZestFinance uses machine learning techniques and large-scale data analysis across a range of sources to make more accurate credit decisions. Vast amount of data sources ZestFinance uses thousands of indicators to assess customer credit scores, not like most American banks relying on FICO credit scores, thought to be based on 15-20 variables. Zest uses unorthodox measures, e.g. the amount of time spent on the website before applying for a loan Machine learning techniques Its decisioning infrastructure runs dozens of individual underwriting models in parallel and delivers a 40% improvement over the current, best-in-class industry score Unlocking a new market Through improved credit risk assessment, ZestFinance is able to offer loans to people that are not being served by the rest of the industry DiversifyData3
    16. 16. Diversify your data to unlock value How can big companies harness the opportunity? 1. Be open to sharing Unless already out in the open, most organisations with valuable data will expect something in return 2. Ask questions, then look for answers To avoid being overwhelmed by the sheer volume and complexity of data, generate early hypotheses to validate before entering into analysis 3. Confirm value potential before negotiating If possible, exchange low-risk samples of data to be combined to explore the potential for identifying new insights and generating value – before entering into a potentially unnecessary contractual discussion DiversifyData3
    17. 17. Join the Intention Economy “I see it as the economy that arises when customers can express their intentions directly to sellers. And it begins to have a real effect not only on prices and offerings, but on the entire economy at large.” Doc Searls, author, The Intention Economy Customers express intentions directly to sellers The effect of the internet in moving us from a mass- market economy to a personalised one is still to reach its fullest impact Shift from Customer Relationship Management to Vendor Relationship Management When engaging with consumers, businesses will agree to the consumer‟s terms and conditions, rather than the other way round Focus on ‘small data’, not big data New tools will allow consumers to have full control over their personal data and how it is used – managing all their interactions in one place IntentionEconomy3
    18. 18. Join the Intention Economy Case Study: Songkick | Empowering music fans to influence where their favourite acts perform, more effectively connecting supply and demand IntentionEconomy3 Songkick, one of the original high tech start-ups in London's Silicon Roundabout area, provides personalised news about live music events. Their „Detour‟ functionality lets users collectively persuade performers to come to their town. Users pledge to buy tickets People interested in a certain performer coming to town can declare how much they are willing to pay for a ticket. Users are only charged when the concert is confirmed. Taking action Songkick partners with a promoter and contacts the artist. The user is contacted with the confirmed date and ticket price. If the user can‟t make the date of the concert, they are not charged. Catching on Eventful‟s „Demand‟ functionality allows users to declare an event or performance they would like to see locally, and then campaign for others to join their "demand“
    19. 19. Join the Intention Economy How can big companies harness the opportunity? 1. Forget big data There is significant opportunity in doing „small data‟ well – building profitable relationships with customers through managing their personal information more effectively 2. Expect customers to gain more control than they have already The pace of change isn‟t slowing down – social media has given customers a voice and taken control away from companies, but new tools and the continued democratisation of data will bring further empowerment 3. Build capabilities to listen, respond and adapt Accept the new reality and build the skills and competencies to listen and respond to customers in real time, and the internal processes that enable quick changes of direction based on this feedback IntentionEconomy3
    20. 20. Be an artist – and a scientist “The hottest job right now is 'data scientist', but that label is wrong. It's not just about science, it's also about art. The hottest job should be data artist -- those who understand the quirks of data and think through and enjoy the nature of what you're talking about.” Douglas Merrill, CEO ZestFinance (Ex-Google VP Engineering) Statistical analysis needs to be robust… Without question, technical skills are required to gain the most from data analytics and confidently identify relationships and patterns …but only a ‘human’ perspective can understand the real drivers for analytical conclusions But quantitative science alone will miss the cultural and social drivers behind customer behaviours Creative communication wins over audiences Clever data visualisation makes the huge scale of big data manageable and engages audiences in the story ArtistsandScientists3
    21. 21. Be an artist - and a scientist Case Study: Proctor & Gamble | Visualising and communicating operational data to support managers in making better business decisions Procter & Gamble has institutionalized data visualization as a primary tool of management with its „Decision Cockpit‟ Common Visual Language A consistent way of displaying information is especially important in a global organisation such as P&G, where managers move regularly between brands and geographical markets. Data Meeting Spaces P&G has built meeting spaces that it calls "Business Spheres" in over 50 locations where management information is displayed for review and decision-making by groups. Getting ‘beyond the what to the why and how’ Decision-makers shouldn‟t spend time with figuring out what has happened in an important area of operations. They should have time to focus on why it happened and how to address the issue. Good visual displays direct management attention to where it is most needed. ArtistsandScientists3
    22. 22. Be an artist - and a scientist How can big companies harness the opportunity? 1. Hire a broader mix of people Bringing art and science to analysis requires a mix of skills – quantitative and qualitative; logical and intuitive 2. Watch, then analyse Watching how customers behave will help to form hypotheses for why they do what they do – which can then be validated through focused analysis 3. Tell stories Tap into your audience‟s rational and emotional needs to engage them in analysis and insights – distil to key messages and use vivid imagery to communicate robust evidence ArtistsandScientists3
    23. 23. In summary...
    24. 24. If companies don‟t realise the big data opportunity, they will become obsolete Takeaways4 If you remember nothing else.. Generate new revenues from exhaust data Combine data sources to derive value Be an artist and a scientist Give people the tools to tell you what the want
    25. 25. 29 Wootton Street, London SE1 8TG. | Big Data | Taming the Data Monster Robin Scarborough +44 (0)7538 406662
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