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8/12/2019 Masters of Machines
http://slidepdf.com/reader/full/masters-of-machines 1/1
MASTERS OF
MACHINES
BUSINESSES NEED MORE KNOWLEDGE
HOW MATURE IS YOUR INDUSTRY?
82%of European businesses believe they could
benefit from the use of operational intelligence
(OI) by collecting, storing and analyzing
real-time and historical machine data to gain
insights that would not otherwise
be available
The “OI Maturity Index” ranges from near zero (no capability at all) to 3 (fully capable in
all areas). The index rates their ability to search and investigate, proactively monitor,
provide operational visibility, and deliver real-time business insights from big data.
When it comes to operational intelligence maturity, industries are ranked in the
following order:
IS SIZE RELEVANT?Some smaller organizations are as capable as larger enterprises; this is due to real need
but may also reflect the fact that they may have less complex IT infrastructures. Smaller
companies may also be more innovative, for example in gaming, and may have
development/IT teams that are more agile than other sectors and potentially more
predisposed to using disruptive technologies.
LEADER OR LAGGARD?
The way machine data is collected and turned into operational intelligence progresses
from IT-focussed root cause analysis to real time business insights. Most organizationsstart at stage one and mature over time through stages 2, 3 and finally 4. The degree to
which they achieved this can be thought of their operational intelligence maturity and is
expressed as the “OI Index”...
INSIGHT OR BLURRED VISION?
83% of organizations admit that they would like to improve, or aren't currently seeing,real-time business insight from their machine data. Across European businesses, who is
believed to have a comprehensive view of their operational intelligence?
2.23
TELECOMS
1.98
FINANCE
1.92
RETAIL, TRANSPORT
AND DISTRIBUTION
1.91
GAMING
1.90
OTHER COMMERCIAL
1.82
MANUFACTURING
1.92Overall, European companies scored an average of
Operational intelligence rating by company size across Europe
– between poor and some capability
Telecoms and finance
stand out because they are more ‘transactive’ than other industries, with 111,000 and 66,000
IT-driven transactions per day respectively which generate considerable machine data, compared
to an average volume of 40,445
Infographic by Michael Agar Design | michaelagar.co.uk
METHODOLOGY
Quocirca surveyed 380 key decision-makers across Europe in January 2014; 99 from France, 97 from Germany,
93 from the UK, 46 from Sweden, and 45 from the Netherlands.
1
2
3
SEARCH AND INVESTIGATE• Capture, store and search machine data
• Search and find the root cause of important events• Analyze machine data to find the root cause of
important events
PROACTIVE MONITORING
• Analyze machine data to notice and manage
exceptions before they impact users or service delivery
• Use machine data in real time to make decisions
about tuning IT systems
• Use machine data to provide the business insight
OPERATIONAL VISIBILITY • Use machine data to measure service levels and key
performance indicators to better serve the business
• Use machine data to gain end-to-end visibility of
consumer behaviour and business performance
• Examine machine data for general intelligence about
customers that would not otherwise be available
REAL-TIME BUSINESS INSIGHTS• Correlate machine data with business data to
provide real-time insight
• Use real-time analytics from machine data to
detect patterns, identify trends and predict
outcomes
• Provide the business views from machine data
analysis that drive real-time decision making with
customer, marketing and product-centric insights
4
35% 28%
56%
True operational intelligence uses the datagenerated by machines to access, tune andimprove IT and business processes, identify
security threats, highlight performanceissues and spot emerging customer trends
BOB TARZEY ANALYST WITH QUOCIRCA
Marketing
Managers
Board-level
executives
IT ManagersProduct
Managers
27%
Overall
1.92Over 5,000
employees
2.153,000 to 5,000
employees
1.921,000 to 3,000
employees
1.80200 to 1,000
employees
2.13