Value Creation for SMBs with Big Data

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We studied impact of the Big Data phenomenon on SMBs.
We conducted interviews among 30 SMBs to check:
- Big Data understanding by SMBs
- Adoption level of Big Data services
- Value creation and go-to-market channels
- Pain points in adopting Big Data

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Value Creation for SMBs with Big Data

  1. 1. VALUE CREATION FOR SMBs WITH BIG DATA by: Andrey Sadovykh, Paul-Emile Poisson, Aleksei Papin
  2. 2. Summary 1. Big Data Phenomenon • Understanding sources and trends of the phenomenon • Overview of the Big Data market and SMB sector 2. Big Data Service Providers • Current services in the market for SMB (bird’s eye view) 3. SMBs Survey • SMB Segments • Understanding Big Data • Value Creation and Go-To-Market • SMB Pain Points for Big Data • SMB Trends 4. Recommendations and Lessons Learnt © Sadovykh, Poisson, Papin, 2014 2
  3. 3. PART #1: BIG DATA PHENOMENON 3
  4. 4. Big Data = Volume + Variety + Velocity Big data is commonly characterized by three vectors: Volume = sheer amount of data Variety = polystructured nature = text, audio and video Velocity = rate at which it is generated and analyzed Source : IDC & EMC 4
  5. 5. Data grows exponentially By 2020, the digital universe will amount to: over 5,200GB per person on the planet In December 2012 the size of the digital universe (that is, all the digital data created, replicated and consumed in that year) was estimated to be 2 837 Exabyte (EB) - Forecasted to grow to 40,000EB by 2020 One Exabyte = 1 000 petabytes (PB) One Exabyte = 1 000 000 terabytes (TB) One Exabyte = 1 000 000 000 gigabytes (GB) Source : IDC & EMC 5
  6. 6. Only ½ % of Data is analyzed Not all of data generated will be actually useful In 2012, 2 837EB generated - just ½% actually analyzed. That still amounts to 14EB (or 14.185 million terabytes) Source : IDC & EMC 6
  7. 7. Practically all that we do creates data 1. 2. 3. 4. 5. Number of @-mails sent every second : 2,9 million Video uploaded to YouTube every minute: 25 hours Data processed by Google every day: 24 petabytes Tweets per day: 50 million Products ordered on Amazon per second: 73 items 7
  8. 8. How big is the market? The chances are, though, that big data will take its place in the mainstream of IT activities. Big Data Pure Players Revenues 25 $(Billions) 20 15 10 5 0 2010 2011 2012 2013 2014 2015 2016 In March 2012 it was forecasted that big data will become a $17 billion market by 2015 (since updated to $23.8bn by 2016 ) Source : IDC & EMC 8
  9. 9. SMBs generate almost 60% of added value Small business, but big revenues • SMBs are 99,8% of enterprises in Europe • 58,6% of revenues is generated by SMBs • Easier to penetrate, low entry barriers, a lot of working domains Source : EuroStat 9
  10. 10. SMBs can leverage Big Data 1. Big Data phenomenon is driven by accelerated growth of the unstructured data. 2. Traditional analytics means cannot cope with such volumes, variety and velocity of data. 3. Proliferation of Cloud computing and Software-as-a-Service made it possible for appearance of affordable data analytics tools for SMBs. © Sadovykh, Poisson, Papin, 2014 10
  11. 11. PART #2: BIG DATA SERVICE PROVIDERS 11
  12. 12. Data, Platforms, Analytics, Applications Platforms Visualization / Analytics Marketing Analytics Ads Targeting Fraud Detection / Costs Data Providers © Sadovykh, Poisson, Papin, 2014
  13. 13. Findings Marketing analytics is a mature industry with many players addressing SMB sector Business analytics: companies can build their own data analytics and reporting on the web from ready to use building blocks. Managed services for business specific statistical models start to appear with the first results in fraud detection or climate fine forecast. © Sadovykh, Poisson, Papin, 2014 13
  14. 14. PART #3: SMB SURVEY 14
  15. 15. Big Data phenomenon understanding 32 SMBs participated in our survey about: Value creation and Go-To-Market SMBs’ pain points Trends 15
  16. 16. We interviewed SMBs from different sectors. Most interviewed SMBs are micro companies and IT related. SMB Revenues 4% <200 K€ 17% 48% 10% 14% 7% 200 K€ to 500 K€ 500 K€ to 1 M€ SMB Sectors 0 2 4 6 8 10 IT services Medical services Media and advertisement E-commerce Finance Computer Hardware and Software Design Games Software editor International phone calls Mathematical modelling Real estate 1 M€ to 3 M€ 3 M€ to 10 M€ > 10 M€ Packaging Import/Export services © Sadovykh, Poisson, Papin, 2014 Non-IT SMBs 16
  17. 17. 56% 44% Most SMBs associate Big Data value with Web Services for Data Analytics 33% 22% Web Service for Data Analytics Data Processing Tools for Developers Not agree © Sadovykh, Poisson, Papin, 2014 Agree 17
  18. 18. 78% 74% Statistical Models and Data Integration bring the most value to SMBs 56% 19% 19% 7% Data Statistical Visualization Models Not agree © Sadovykh, Poisson, Papin, 2014 Data Integration Agree 18
  19. 19. Not all SMBs managed to apply Big Data 38% do not use Data Analytics © Sadovykh, Poisson, Papin, 2014 19
  20. 20. Sales increase preoccupation prevails 67% 56% 22% Sales increase Cost Risk reduction reduction © Sadovykh, Poisson, Papin, 2014 20
  21. 21. SMBs struggled to provide quantifiable ROI indications © Sadovykh, Poisson, Papin, 2014 21
  22. 22. 54% of SMBs mainly employ internal resources for Data Analytics implementation Who implemented Data Analytics? no data analytics 39% our employees consultants 54% 7% © Sadovykh, Poisson, Papin, 2014 22
  23. 23. Information Channels 13 SMBs prefer Web sites to learn about Big Data 6 6 5 3 News WebSites Blogs © Sadovykh, Poisson, Papin, 2014 Conferences Press IT Consulting 23
  24. 24. Procurement Channels 80% of IT SMBs prefer to buy through selfservice web channels 12 3 2 Web-site IT Consulting © Sadovykh, Poisson, Papin, 2014 Sales reps 24
  25. 25. For Non-ITs: “Sales representatives bring value” © Sadovykh, Poisson, Papin, 2014 25
  26. 26. Budget limitations Potential pain points for Big Data at SMBs Lack of employees experienced Risk aversion, need for ROI guarantees in Big Data Difficulty to formulate right questions, need for guidance Security concerns Extreme variety of data Need for very custom solution © Sadovykh, Poisson, Papin, 2014 26
  27. 27. • 59% consider important budget limitations at SMBs • 55% indicate ROI guarantees as highly desirable • 59% report lack of personnel experienced in Big Data and Data Analytics as a potentiall blocking point © Sadovykh, Poisson, Papin, 2014 27
  28. 28. • 59% report that SMBs need guidance when dealing with Big Data • 59% consider security aspects important. • Though, non-ITs are ready to rely on data centers. • 55% indicate data variety concerns • 69% report the need for very custom solution. © Sadovykh, Poisson, Papin, 2014 28
  29. 29. SMB Trends for 2014 62% hope to grow revenue by11% 44% estimate data traffic grow by 30% 54% think to grow data storage by 30% 81% estimate that their infrastructure is ready © Sadovykh, Poisson, Papin, 2014 29
  30. 30. PART #4: RECOMMENDATIONS 30
  31. 31. Recommendations Clearly explain ROI gains when addressing SMB market. Concentrate on turn key services. Provide scalable self-services to SMBs. Start adopting Big Data from marketing analytics. Cost and risk reduction services are largely untapped. © Sadovykh, Poisson, Papin, 2014 31
  32. 32. BIG DATA COULD BE THE SOLUTION FOR YOUR BUSINESS TOMORROW… 32
  33. 33. Contacts • For further information and full report please contact: • Andrey.Sadovykh@hec.edu • Paul-Emile.Poisson@hec.edu • Aleksei.Papin@hec.edu This presentation is prepared in the context of the consulting project conducted by HEC Paris Business School © Sadovykh, Poisson, Papin, 2014 33
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