BIG DATA ANALYTICS: CHANGING THE WAY YOU DO BUSINESS

Transcription

1 BIG DATA ANALYTICS: CHANGING THE WAY YOU DO BUSINESS John Morton Data Science MSC Goldsmiths UoL London March /03/2016 1

2 Title Big Data Analytics: Changing the way you do business Description Having great technology and being analytic skilled are key skills demanded from the market place. This discussion is focussed on how you help business and organisations understand the value of data, effectively use data or disrupt established industries. This presentation covers new business models and uses for Big Data, Open Data and Your Data within organisations. John Morton has 30 years experience in delivering information exploitation solutions in a range of industries, runs a consultancy company advising on Disruptive technologies like Big Data and mentors and advises on a number of start-ups, five of which are exploiting open and Big Data. 23/03/2016 2

3 BIG DATA HYPE OR, SOMETHING REAL?.. and more.. 23/03/2016 3

4 .OR THEORY? Velocity Variety Volume Value Gartner /03/2016 4

5 TRIED AND TRUSTED Reduce multiple reports to allow clear decision making Complex inter-relationships visible Dynamic visualization for interactive data exploration and visual queries "If the rate of change on the outside exceeds the rate of change on the inside, then the end is near." -Jack Welch 23/03/2016 5

6 WHY ALL THE INTEREST?. US healthcare reduction by $300 Bn a year 2/3rds from a 8% reduction in national healthcare retailers can increase operating margin by 60% by fully utilising data 100 Bn reduction in Government administration across Europe... predict the buying behavior and decision criteria of your prospects weeks before your competition... gain first-mover advantage by introducing new products and services to micro market segments that haven't been identified by anyone... evaluate the impact of your marketing campaigns hourly and make adjustments in real-time Sustain a 4 to 6 % in efficiency and effectiveness over your competitors 23/03/2016 6

7 BIG DATA VALUE HYPE? 216 Billion in 5 years, 58,000 jobs * Creativity: Innovation: 42 Billion 150 Billion Productivity: 124 Billion *UK CEBR - Center for Economics and Business Research 23/03/2016 7

8 Is Big Data for everyone? IBM in $2bn deal for Weather Company digital unit Relative contribution to GDP Source : US Bureau of Labor Statistics; McKinsey Global Institute Analysis 23/03/2016 8

9 ABOVE: Types of industry sectors where companies are using open data in their businesses, sourced from OpenData /03/2016 9

10 HAVE THEY MISSED THE BOAT? 34% of respondents were drawn from North America, 43% from Europe 23/03/

11 SO WHAT ABOUT TECHNOLOGY? Technology shift 30 Terabyte disks 2000 fault tolerant, My computers data Store everything file systems In-Memory Integr In-Database processing ated Data In-Memory Analytics In-Chip Analytics Your data Visualisation of data Open data Massively-parallel processing (MPP) analytics HPC versus HPT 23/03/

12 BUSINESS DILEMMA How can we increase productivity? What more can I do to compete? Staying in business What else can we do? 23/03/

13 BIG DATA DISRUPTION 23/03/

14 STAYING IN BUSINESS productivity Stay Transparency Security Business Health Provenance Compliance Governance Business Improvement Integrated Data My data 23/03/

15 DOING MORE WITH WHAT YOU HAVE productivity compete Missed Opportunities Wasted Effort Don t forget Data Quality 23/03/

16 Lets talk about Decisions.. Observe Orient Decide Act 23/03/

17 Analytics Changes the Process productivity compete Observe Orient Decide Act Observe Orient Decide Streamlined processes Decision driven steps Data and process aligned Moving to Exception Management Act COMPETITIVE ADVANTAGE BUSINESS OPPORTUNITY 23/03/

18 NEW BUSINESS Application Services New Integrat ed Data My data Open data Business Rules Analytics Anomaly Detection Predictive Modeling Exploitation Transparency Process Security Alert Administration Health of business Provenance Value Analysis Rules Analytics Your data Learn and Improve Cycle Management & BI / Reporting Case Management 23/03/

19 OPERATING MODEL CEO Function Function Function Functio n CEO Functio n Function Functio n Functio CEO n Function Function Function Function Function Leading analytics CMO + CIO + CPO + COO 23/03/

20 Knowledge and Cognition BIG DATA FRAMEWORK Communication and Collaboration Governance and Analytic Realisation Culture Value Action Performance and Assessment Analytics Mindset and Business transformation Learning and development Competence Centre Data Support Services Enabling Infrastructure Taking Action Integration Interpretating data Methods Tools Predictive and Scenario Analysis Decision Making Analytics as a Service Data as a Service 23/03/

21 Knowledge and Cognition BIG DATA FRAMEWORK Communication and Collaboration Governance and Analytic Realisation Culture Realising Value Learning and development Competence Centre Data Support Services Enabling Infrastructure Value Action Performance and Assessment Mindset and Business transformation Developing Capability Taking Action Integration Interpretating data Methods Tools Analytics Discovering Diamonds Predictive and Scenario Analysis Decision Making Analytics as a Service Data as a Service Prowess 23/03/

22 ANALYTICS SUPPORTING PRICING Business as Usual Prices are set regionally or by products Promotional pricing offered on new term deposits When promotional pricing lapses Some customers leave Other roll-over their deposits Promotional and go-to prices vary significantly Across regions Over-time Relative to competition Analytic pricing Statistically predict customers sensitivity by product by price to pricing strategy Target the right price for the customer Consciously manage the fund for customer retention 23/03/

23 MARKET BASKET ANALYSIS Classical Advanced next product to Buy Basket = Collection of Customer Specific data that may include: Socio-demographics Product portfolio Transactional Behaviour Contact history Debt and payments history 23/03/

24 RECOMMENDATION ENGINES Revenue 5-15% overall revenue increase Engagement 12 18% of visitors engaged with product recommendations Average Order Value 30-70% increase visitors who engage with recommendations Conversion Rate 2-4x increase visitors who Saving Staff Time Elimination of manual Content Management effort Items per Order 20-40% increase- visitors who engage with recommendations 23/03/

25 CROSS CHANNEL INTEGRATION Multiple customer touch points each with its own Infrastructure, islands of data, isolated points of knowledge. Brings Diverse Data sources together Organises into meaningful customer journeys Non standard business process Service and dispute resolution 23/03/

26 CROSS CHANNEL INTEGRATION VALUE Challenge : Which offer should be made to the customer through which channel at which time? However you have to take care of: Budget- and/or Resource restrictions Limit of customer contacts (Customer Contact Strategy) Strategic Changes (You have to push Product A!) Unsatisfying response- or sales figures or unbalanced channelusage Customer buying practice Customers sensitivity to price

27 (a) (b) Figure 1: (a) the data scientist (Conway, 2011); (b) business analytics (Robinson, 2014) 23/03/

28 BUSINESS ANALYTICS ECO-SYSTEM Data assets Value propositions ICT strategy Analytics strategy Business strategy HR strategy Vidgen, R., (2014). Creating business value from Big Data and business analytics: organisational, managerial and human resource implications. Hull University Business School Research Memorandum, no. 94, ISBN /03/

29 PARTING THOUGHTS 1. Can I trust that the technology chosen is going to get the best out of my data? 2. What are the trade-offs between the algorithms employed by service A versus service B? 3. If the solution claims to be automated analytics, how robust is that automation? 4. Is the technology extensible and interoperable to meet changing demands from data, evolving business, or competition? 23/03/

30 QUESTIONS Questions?. Eur. Ing. John Morton BSc, CEng. FBCS, CITP, MIoD Twitter: JohnFMorton 23/03/