finding value in the digital maze data driven finding value in the digital maze

@ToufiqAbrahams Consultant Solution Provider Data strategy Data architecture Data models Information delivery Solution Provider IoT Analytics Mobile BPM Analytics Hosted Analytics

how much is your data worth? The Microsoft acquisition of Linked In is a definitive statement of the value of data. Perhaps the biggest competitive advantage for the digital era is the ability to convert data into business value.

how do we get value from data? Data = it starts with the ability to generate/harvest data points Information = classification of data Knowledge = understanding the relationships between classified data Insight = definition of key metrics (ability to measure) Wisdom = understanding the correlation between metrics (patterns in the data) Image by David Somerville

digital industrial revolution Steam Power MECHANISATION Electrical Power MASS PRODUCTION Computing Power AUTOMATION Cyber Physical Systems SMART AUTOMATION 1 2 3 4 The value of data is even more pertinent with the onset of the 4th industrial revolution. Data fuels the “smart” in smart automation 1784 – First Mechanical Loom 1870 – First Assembly Line (Cincinnati Slaughter House) 1969 – First Programmable Logic Controller (PLC) Now – Smart Automation (AI)

the road to 4.0 4.0 2006 2007 2008 2009 2010 2011 2012 2006 – Amazon Elastic Compute Cloud (EC2) 2007 – Smart phones (iPhone) 2008 – LTE networks 2009 – Mongo DB (DB model for the mobile world) 2010 – Azure (Microsoft Cloud) 2011 – Hadoop (Hadoop Distributed File System) 2012 – Nexus of Forces (connecting the dots between mobile, social, information and cloud)

Gartner – Nexus of Forces “…convergence and mutual reinforcement of four interdependent trends…” “… transforming the way people and business relate to technology…” “…To take advantage of the Nexus of Forces and respond effectively, organizations must face the challenges of modernizing their systems, skills and mind-sets…” Conceptual precursor to Digital Industrial Economy

digital disruption Consumer culture change Virtual business models Connected everything Virtual business models Facebook, Uber, Airbnb Technology service models IaaS PaaS SaaS

big data: focus on value Connected Everything Internal Consumers Big data is an ambiguous term, but what is clear is 3 key streams of data: Traditional: transactional data from business processes (still the most valuable, still too often not realised value) IoT: a new way to optimise processes (not only business) by adding sensors and analysing Social: the hardest value add is understanding sentiment and behaviour (relies on digital/social presence) Devices Sensors Business Processes (transactions) Opinions Facts Facts Opinions Qualitative Quantitative Quantitative Qualitative Complex Value Intrinsic Value Known Value Hidden Value

new data sources & challenges Mobile BPM IoT Gateway Complex Subject Areas Difficult to model Organizational speed Complex Data Structures Unstructured/semi-structured Granular Complex Analysis Sentiment/Natural Language Behaviour Social AI For the analytics world we have 4 new data sources that come with their own complexities

data landscape Reporting Data Viz Mobile Sales Data Warehouse ETL Finance Analytics Advanced Analytics HR Document DB The traditional BI landscape becomes more complex, but cloud services offer some relief in abstracting complexity. Mobile Platforms API Hadoop Machine Learning Event Hub Social Media

data consumer landscape Cloud (public and private) enables a more fluid combination of business process execution and measurement … the true value of this is “information at the point of decision”

enabled anywhere abstract complexity enablement elastic scale enabled anywhere abstract complexity BUSINESS VALUE Cloud services pushes compute power to the cloud while you BYOD as a presentation and interaction tool.

responsible adoption Scale of computing – new possibilities Understand impact & filter out hype BI services, platforms and tools – extremely capable Select for function, ease of use, integration & cost Methodologies/approaches/techniques – tried & tested Adapt to fit your requirements & culture Skills and expertise - limited availability & expensive Select carefully, nurture & develop

goal posts have not shifted What happened? What we would like to happen? State of the Business What is likely to happen? Why did it happen? Make Informed Decisions Develop New Insights Predict the Future

driving change Find NEW Value Find Value QUICKLY Agility vs. Control

where are you stuck? unhappy customer struggling business

data driven Social Man happy customer smart business