business analytics, part i introduction presented by scott koegler editor, ec-bp.org
TRANSCRIPT
Business Analytics, Part IIntroduction
Presented by Scott KoeglerEditor, ec-bp.org
Business Analytics
• Business Analytics• What is it?• Where did it come from?• What is it supposed to do?
BI – A Starting Point
• Business Intelligence (BI) • Discovering what happened• Look at past events• Typical of ERP reports
BI & BA
• What differentiates BA from BI?• Looking forward• Trend moving to predictions• Predictive analysis
BA & Data
• Data is the key to BA• Lots of data• Real-time or near-time• Widest collection
of data
Challenges
• Data?• Access?• Reporting?• Outcomes?
Why Is BA a Hot Topic?
• Optimization is the new growth
• Expansion was the best way to grow• Now too expensive• Difficult to open new
markets
Not About the Tools
• Tools do exist• Know the desired
outcomes
Outcomes
• Outcomes define the project• Stakeholders must drive the quest• Business in / technology out
How Far to Reach
• Not far-reaching• Best to start
with smaller goals• Tactical goals first
Possibly Too Limited
• Analytics are not in a box• Think of analytics as part
of the holistic environment• Tactical goals are part of
the overall plan
Leakage
• Organizational process leakage• The key findings may be
lost along the way
Focus on the Delta
• Difference between:• Current situation• What is possible
Close the Gap
• The Gap is the difference between what is and what is possible• Don’t worry about closing
the gap completely• Incremental improvements
do count
80/20 Rule Applies
• Determine the most important changes
• Monitor progress• Evaluate the results
Good Enough
• Good enough is good enough
It’s a Process
• BA is not “buy and push the button”
• Every implementation is different
• Tools for custom outcomes
Processes
• Create numerical results• Implement in meaningful ways• Integrate outcome to technology• Integrate • Monitor and fine-tune
Refine & Evaluate
• Continuous loop• Measure the Gap• Fix what doesn’t work• Measure the Gap• …
Categories of Analytics
• Descriptive Analytics• Prepares and analyzes
historical data• Identifies patterns from
samples for reporting of trends
Categories of Analytics
• Predictive Analytics• Predicts future
probabilities and trends
• Finds relationships in data not readily apparent with traditional analysis
Categories of Analytics
• Prescriptive Analytics• Evaluates and
determines new ways to operate
• Targets business objectives and balances all constraints
Limits to Predictions
• Long-term projections are difficult• 5- to10-year projections• Changes are difficult to
predict
Barriers to Achievement
• Massive amounts of data• Need for real-time access• Traditional data in
transactional systems• Requires optimized
computing platforms• Disk drives can’t keep up
Combination of Changes
• De-normalized databases• Removes multiple tables• Flat data file
• Optimized data structures• Optimized computing
What About ROI?• ROI is not always immediately obvious• Results of analytics may be available only
after years of following the prescription• Requires long-term efforts
Returns Defined
• Viable Business Analytics• Results based on the business• Define the desired results• Agree on definition of success
Recommendations
• BA initiatives are different• Commonality is in the approach• Treat BA as any project• Generally longer term
• Iterative process• Constant updates
Recommendations
• Monitor progress• Focus on outcomes• Review validity• Revise data collections
Analytics Everywhere
• Increasingly used• Volume of data collected driving use• Optimization of business = growth• Look for opportunities
• Data collection• Future outcomes• Uncertainty