Beyond Dashboards
15 September, 2016
Silicon Valley
@soody
http://www.slideshare.net/ssood/foresight-analytics
2
Insights-driven businesses will
generate $1.2 trillion in 2020
Forrester Research, 2016
3© 2016 Forrester Research, Inc. Reproduction Prohibited
Insights-driven businesses are faster than large companies
$0
$250
$500
$750
$1,000
$1,250
2015 2016 2017 2018 2019 2020
Revenue (billions)
Public
Startup
Global GDP will grow
only 3.5% annually.
27% CAGR
40% CAGR
Source: Forrester, Morningstar, PitchBook, and The Economist Intelligence Unit
Reports
&
Analysis
Visualisation
&
Interpretation
Write
Data/Business
“Story”
Insights
Led by Data Analyst or Scientist
SME owner, Machine Learning and Natural Language Generation
Fusion of data science, business knowledge & creativity for maximium ROI
Data
Aggregation Operationalise
Detect & Extract
Patterns and
Relationships
Generate Insights
&
Story
Process
Application
IoT
Data
Aggregation or
Data Set
Traditional Analytics: Slow & Expensive
80% of time sifting through data
System of Insight (SoI)
SoI: Fast & Cost Effective
80% of time in decision making with client
New Sources of Information (Big data) : Social Media + Internet of Things  Innovations
7,919 40,204
2,003,254,102 51
Gridded Data Sources
CCTV
6
7
https://nodexl.codeplex.com/
8
Sherman and Young (2016), When Financial Reporting Still Falls Short,
Harvard Business Review, July-August
Sood (2015), Truth, Lies and Brand Trust The Deceit Algorithm,
http://datafication.com.au/
New Analytical Tools Can Help
9
http://www.analyzewords.com
Actionable Insights
1. What now ?
2. So what ?
3. Now what ?
11
Companies are reimagining Business
Processes with Algorithms and there is
“evidence of significant, even exponential,
business gains in customer’s customer
engagement, cost & revenue performance”
Wilson, H., Alter A. and Shukla, P. (2016), Companies Are Reimagining Business Processes
with Algorithms, Harvard Business Review, February, https://hbr.org/2016/02/companies-
are-reimagining-business-processes-with-algorithms
Better customer experiences . . .
. . . and half the inventory-carrying costs
of other online fashion retailers.
Forrester, 2016
Systems of Insight
 Automated pattern extraction
 Outlier detection
 Correlation
 Time series
 Analytics integration with process, app or IoT
https://ubereats.com/melbourne/
14
outlier-detection “allow detecting a significant fraction
of fraudulent cases…different in nature from historical
fraud…resulting in a novel fraud pattern”
Baesens, B., Vlasselaer, V., and Verbeke, W., 2015, Fraud Analytics Using Descriptive, Predictive,
and Social Network Techniques: A Guide to Data Science for Fraud Detection, Wiley
The ANZ Heavy Traffic Index comprises
flows of vehicles weighing more than 3.5
tonnes (primarily trucks) on 11 selected
roads around NZ. It is contemporaneous
with GDP growth.
The ANZ Light Traffic Index is made up of
light or total traffic flows (primarily cars and
vans) on 10 selected roads around the
country. It gives a six month lead on GDP
growth in normal circumstances (but cannot
predict sudden adverse events such as the
Global Financial Crisis).
http://www.anz.co.nz/about-us/economic-markets-research/truckometer/
Systems of Insight
• Helps move away from “crisis levels” in talent
• Traditional 5 step analytics process reduced to 2 step from data to action
• Reimagine business processes through “machine engineering”
• Minimise messy data issues and data preparation time
Next Step
Start using Systems of Insight and innovative data sources
Vs
Just dashboards

Beyond dashboards

  • 1.
    Beyond Dashboards 15 September,2016 Silicon Valley @soody http://www.slideshare.net/ssood/foresight-analytics
  • 2.
    2 Insights-driven businesses will generate$1.2 trillion in 2020 Forrester Research, 2016
  • 3.
    3© 2016 ForresterResearch, Inc. Reproduction Prohibited Insights-driven businesses are faster than large companies $0 $250 $500 $750 $1,000 $1,250 2015 2016 2017 2018 2019 2020 Revenue (billions) Public Startup Global GDP will grow only 3.5% annually. 27% CAGR 40% CAGR Source: Forrester, Morningstar, PitchBook, and The Economist Intelligence Unit
  • 4.
    Reports & Analysis Visualisation & Interpretation Write Data/Business “Story” Insights Led by DataAnalyst or Scientist SME owner, Machine Learning and Natural Language Generation Fusion of data science, business knowledge & creativity for maximium ROI Data Aggregation Operationalise Detect & Extract Patterns and Relationships Generate Insights & Story Process Application IoT Data Aggregation or Data Set Traditional Analytics: Slow & Expensive 80% of time sifting through data System of Insight (SoI) SoI: Fast & Cost Effective 80% of time in decision making with client
  • 5.
    New Sources ofInformation (Big data) : Social Media + Internet of Things  Innovations 7,919 40,204 2,003,254,102 51 Gridded Data Sources
  • 6.
  • 7.
  • 8.
    8 Sherman and Young(2016), When Financial Reporting Still Falls Short, Harvard Business Review, July-August Sood (2015), Truth, Lies and Brand Trust The Deceit Algorithm, http://datafication.com.au/ New Analytical Tools Can Help
  • 9.
  • 10.
    Actionable Insights 1. Whatnow ? 2. So what ? 3. Now what ?
  • 11.
    11 Companies are reimaginingBusiness Processes with Algorithms and there is “evidence of significant, even exponential, business gains in customer’s customer engagement, cost & revenue performance” Wilson, H., Alter A. and Shukla, P. (2016), Companies Are Reimagining Business Processes with Algorithms, Harvard Business Review, February, https://hbr.org/2016/02/companies- are-reimagining-business-processes-with-algorithms
  • 12.
    Better customer experiences. . . . . . and half the inventory-carrying costs of other online fashion retailers. Forrester, 2016
  • 13.
    Systems of Insight Automated pattern extraction  Outlier detection  Correlation  Time series  Analytics integration with process, app or IoT https://ubereats.com/melbourne/
  • 14.
    14 outlier-detection “allow detectinga significant fraction of fraudulent cases…different in nature from historical fraud…resulting in a novel fraud pattern” Baesens, B., Vlasselaer, V., and Verbeke, W., 2015, Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection, Wiley
  • 15.
    The ANZ HeavyTraffic Index comprises flows of vehicles weighing more than 3.5 tonnes (primarily trucks) on 11 selected roads around NZ. It is contemporaneous with GDP growth. The ANZ Light Traffic Index is made up of light or total traffic flows (primarily cars and vans) on 10 selected roads around the country. It gives a six month lead on GDP growth in normal circumstances (but cannot predict sudden adverse events such as the Global Financial Crisis). http://www.anz.co.nz/about-us/economic-markets-research/truckometer/
  • 16.
    Systems of Insight •Helps move away from “crisis levels” in talent • Traditional 5 step analytics process reduced to 2 step from data to action • Reimagine business processes through “machine engineering” • Minimise messy data issues and data preparation time
  • 17.
    Next Step Start usingSystems of Insight and innovative data sources Vs Just dashboards