Class 17 and 19 Flashcards

1
Q

future of the distribution industry (3)

A
  • increased use of alternate sourcing (less overseas)
  • shrinking workforce
  • more technology (robotics, AI)
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2
Q

concerns of distributors in 2023 and 2024 (5)

A
  • supply chain and inventory
  • customer spending and market demand
  • economic uncertainty and recession
  • labor/staffing
  • pricing, inflation, and costs
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2
Q

how to play offense in defensive time (5)

A
  • evaluate last price paid
  • invest in innovation
  • react to threats and opportunities quickly
  • get a better buy price
  • make a value creation plan with key suppliers
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3
Q

geopolitical unrest countries (7)

A
  • Israel
  • Ukraine
  • Russia
  • China
  • Iran
  • north Korea
  • Mexican cartels
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4
Q

its not what you know, its…

A

what you do with what you know

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5
Q

why business analytics?

A
  • bridges the gap between what is currently happening and what do you want to happen
  • helps identify the problem
  • provides tools to help solve the problem
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6
Q

4 reasons to use analytics

A
  • measure company performance
  • make better decisions
  • understand your customers activity
  • give customers exactly what they want
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7
Q

definition of business analytics

A

practice of iterative methodical exploration of an organizations data with emphasis on statistical analysis. DATA DRIVEN DECISION MAKING

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8
Q

value of business analytics to a distributor (3)

A
  • tell you what has happened
  • helps you determine what you want to happen
  • provides a path to your desired destination
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9
Q

three types of business analytics

A
  • descriptive
  • predictive
  • prescriptive
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10
Q

question answered by descriptive analytics

A

what has happened?

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11
Q

question answered by predictive analytics

A

what will happen?

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12
Q

question answered by prescriptive analytics

A

what should we do?

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13
Q

successful business analytics depends on…

A

data quality, skilled analysts, and commitment

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14
Q

What are tools for descriptive analytics (5)

A
  • reporting
  • dashboards
  • scorecards
  • segmentation
  • clustering
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15
Q

What are tools for predictive analytics (3)

A
  • data mining
  • modeling
  • forecasting
16
Q

What are tools for prescriptive analytics (3)

A
  • optimization
  • simulation
  • big data analysis
17
Q

4 analytics challenges

A
  • not having complete data
  • not factored into budget
  • we are already successful, why do we need analytics attitude
  • we dont have the bandwidth to implement
18
Q

top reasons for using analytics (4)

A
  • gain competitive edge
  • make better informed decisions
  • build better strategy
  • knowledge and experience are no longer sufficient
19
Q

top challenges to making business analytics work

A
  • not focused on what really important (customers & products = profit)
  • data not present in relevant manner
  • ERP not set up to make data easily accessible
20
Q

7 Practical steps for making business analytics work

A

1) expand the use of business analytics where feasible
2) integrate analytics across organization
3) deploy analytics on specific business tasks
4) create a management strategy that includes ready access to data
5) deliver and communicate value
6) hire and develop the right analytical talent
7) use business analytics in decision making process

21
Q

3 usual analytics

A
  • financials
  • sales
  • inventory
22
Q

this is why we use business analytics to make…

A

better informed decisions and integrate technology to enhance our operations as a distributor

23
Q

why is business analytics important? (5)

A
  • decreased risk with strategic decision-making
  • reveal growth opportunities
  • strategies can be built to increase operational efficiencies
  • can aid in effective human resources decisions
  • improve productivity
24
Q

definition of descriptive analytics

A

the use of data to find out what happened in the past, and what is happening now

25
Q

descriptive analytics can help to identify ____ & ______

A

strengths and weaknesses

26
Q

what does diagnostic analytics answer

A

the why of descriptive analytics