1. POS Analytics & Querying
Timothy Dunham
March 23, 2017

2. Agenda Starts with Querying Importance of Verifying Result Set
Importance of Understanding Drivers of Behavior
Partnering with Business Partners
Translating Data into Actionable Intel for Non- Technical Coworkers
Common Looks
Dashboards

3. Starts with Querying Data Resources & Developing Reporting
Knowing how your data is stored and how to retrieve it is key
Understanding the relationships of your database is critical
Having a great data dictionary and other resources help create effective queries
Having great understanding of the business and the problems that the business is faced with is the foundation to great insight and reporting
Taking time upfront will translate into saved time at the end

4. Importance of Verifying Result Set
Data Integrity & Verified Results
Your reputation is only as good as the data you present
Confidence is lost quickly with incorrect reporting
Correctness is critical when completing investigations
Livelihood & freedom on line at times
Piecemeal query creation is key to ensuring new logic does not corrupt result set
Raw system verification is also key to ensure data integrity within data repository
Working with team members to ensure that logic and result set makes sense

5. Importance of Understanding Drivers of Behavior
Understanding Behavior
Being able to understand the challenges in your sales environment will greatly increase the effectiveness of your exception reporting
Is it a commission based environment?
How is the company driving the sales reps behavior?
What possible unethical sales situations could arise?
Knowledge of how compensation is determined is also key
Compensation drives behavior
Knowledge of the competitive environment
Is a competitor’s actions going to lead to possible grey areas?
Knowledge of not just the front line sales force, but also what is driving their leadership

6. Partnering with Business Partners
Importance of Internal & External Partnerships
Most are challenged to do more with less these days
Leverage partnerships to distribute the load
Knowledge sharing helps drive uncovered areas and emerging trends
Exposure to other subject matter experts that can provide additional insight
Help identify and drive questionable activity out of the business
Utilize other groups relationships to have system changes and fixes completed

7. Translating Data into Actionable Intel for Non-Technical Coworkers
Developing Actionable Intelligence from Large Datasets
Understand and adjust based on the target audience
Prelim meetings with the requestors to understand their needs and goals
Based on those discussions develop a report that provides the requestor what they need and what they want to see within the report
Ensure that all relevant information is provided to ensure that all needs are met
Provide a simple summary of the findings that is included in the report
Setup a meeting once the report is completed to discuss findings and any additional steps that may make sense based on the findings

8. Common Looks Common Issues/Looks for Retail
Suspect activity prior to fraud
Normalizing the data to identify outliers
Store has lower number of suspect orders, but all completed by same employee
Completing peer to peer analysis
Certain job have increased exposure to certain activities and have to develop baseline
Volume reporting
Does a certain person have dramatically higher sales in one category than another
Shrink Reporting
Provide actionable intelligence to Loss Prevention team to identify problematic stores

9. Dashboards