data

Role of Data in Business Operations

The presenter spends much of their time teaching about data analytics at Deere.
- Emphasis on clarifying available data and its implications for users.
- Approach is to simplify complex data to avoid overwhelming the audience.

Accumulation Graphs:
- Used to track and unfold stories from past data over approximately three years.
- X-axis represents machine age (in months); Y-axis tracks claims up until a saturation point.
- Highlighting issues in reporting and achieving timelines in business accounting.
Differentiation of mathematical concepts:
- Traditional statistics often do not accumulate variables effectively.
- Business math tends to be simpler and focused on monthly and annual reports.

Businesses frequently inquire about current status; graphs facilitate this information.
- Example: 90 claims reported over twelve months, which is lower than previous years.
- Insight drawn that selling fewer machines can correlate with fewer claims.
Emotional Considerations in Data:
- Humans have difficulties remembering past data, leading to optimism without accountability.
- Discusses implications of reducing failures and claims early in the cycle.

The presenter creates multiple visualizations using Tableau, with around eight tabs containing 4-12 visualizations each.
- Importance of training materials:
- Each visualization has an accompanying tutorial video on Panopto.
- Transcripts are provided for non-native English speakers.
- Need for organizations to understand data availability and access methods.

Basic Graph Types:
- Line Graph:
- Used for trend overview.
- Scatter Plot:
- Identifies warranty cost issues and helps visualize where problems may arise.
- Anything above and to the right of a certain line indicates a problem area.
- Reduction of emotional burden on teams dealing with problems.
Pareto Principle:
- 20% of certain machine families may cause 80% of issues.
- Useful for prioritizing focus on key problems rather than superficial issues.
- Real-world application in resource allocation and staffing after layoffs in the company.

Heat Maps:
- Provides visual feedback on number of claims.
- Improvements indicated by a green-to-red scale.
Emotional influence on decision-making is crucial. People often base decisions on emotional reactions rather than rational thinking.

Mention of Technical Assistance Group with thousands of personnel handling dealer issues.
Rolling 12-Month Average:
- Reduces variability in data over time by averaging claims so businesses can identify trends.
- Important for reducing chaos in data interpretation.

Use of running charts and tables to assess machine build quality and problems encountered.
Discussion of a unique dual-Pareto or “tornado” graph design implemented in Tableau.
- Graphs showcase both number of calls and number of problematic machines, aiding better prioritization.