Business Analytics, Part IIntroduction

Presented by Scott KoeglerEditor, ec-bp.org

Scott KoeglerEditor of ec-bp.org

scott@ec-bp.org

Speaker

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