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42 Cards in this Set
- Front
- Back
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billy beane method
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analyze existing data differently
better performance models yield better decisions: - play acquisition - utilization of existing players |
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emergence of management
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prior to 1900 no pro. mgt.
today: pro. mgt. important for social functions (healthcare, education, welfare, econ, etc.); survival depends on good mgt. |
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mgt. 1.0 instinct
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mgr. as gunslinger
- gut feel decisions - company performance depends on mgt. talent - strict org. hierarchy rules |
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mgt. 2.0 decisions
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fact-based decisions
data-driven decision support systems (DDS): database , decision models, interactive and analytical modeling process decision support evolution: better data, models, tech.; pushed lower into org. |
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mgt. 2.0 implications
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reduced reliance on "superstar" mgrs.
DDS enables ordinary people to perform at extraordinary levels what we think vs. what we know competing on analytics |
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competing on analytics
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sophisticated IS and rigorous analysis applied across all company functions
development and maitinence of analytics capability is a primary focus fact-based decisions hire many people with good analytical skills metrics for evaluating key business processes share data and analysis with customers and suppliers small experiments to create a culture of "test and learn" |
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retail industry -- IT-enabled changes
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power shift to large retailers: from push to pull; bulk buying, economies of scale; closer to consumer; control of shelves and extended store chains; store brand recognition and acceptance
product proliferation: excess demand for shelf space; slotting fees; excessive mfg. prod. promotions integration of supply chain partners |
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old retail process
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build buyer relationship -- persuasion tactics to influence decisions -- purchase decision -- ind./ad-hoc decisions (shelf layouts, promotions) -- analysis of results (long lag time and high level aggregation)
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new retail process
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collect and share scanner info. with mfg. -- category review analysis -- reccomend mkt. mix strat. -- data driven strategy decisions -- analysis of results -- mfg. modifies promotion and mkt. strategy
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retail performance review process
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retailer strategy and positioning
growth and mkt. share analysis prod. mix/variety analysis reccommendations |
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DDS process
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database
decision models decision-maker insights interactive analytical modeling process |
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DDS design principles
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reliability: output is correct and consistent
auditability: user able to trace steps to generate output modifiability: easy to modify elegant simplicity: approp. degree of automation; approp. calc./processing method; NOT clever complexity |
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DDS effectiveness test
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purpose: goals, qualifications answered
data: type and qty./source calculations: parts calcuatlated, formulas used changes: easy to modify or change data |
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structured process vs. ad hoc approach
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ad hoc: good for simple model with few deliverables; small data set; BUILDER = USER
structured process (SDLC): good for complex model and system; may deliverables; large data set; BUILDER NOT USER |
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DDS development process
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design
build and test document |
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DDS design - 4 step process
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1. output - metrics, tables and graphs
2. processing logic - models to generate output metrics; excel tools and methods to populate output forms 3. data model - sources, structures, links 4. excel multisheet layout - what goes where in spreadsheets |
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DDS design practices
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goal - elegant simplicity
approach - art, NOT science process - iterate among 4 steps until design goal is met |
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DDS design tips
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work back from end product
catch and fix problems before the spiral out of control acid test: stranger must be able to replicate the analysis with new set of data without help from developer |
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growth market share output forms
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how to measure growth
how to measure market share how to compute for each group how to display results |
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growth rate metrics
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% growth rate for market - (sm05-sm04)/sm04
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market share metric
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market share = sp05/sm05
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growth/mkt. share quadrant chart
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mkt. share vs. growth rate %
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variety product mix output form
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how to measure variety
how to calculate variety for each group how to determine if prime has right mix how to display results |
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variety index ratio
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= # prime SKUs/# market SKUs
top 10 bottom 10 comparison - 10 SKUs with lowest sales - 10 SKUs wit highest sales |
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uses for spreadsheets
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small simple databases
grid for drawing/flow charts financial models stat. analysis project management |
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alt. methods for deliverable processes
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brute force: sort, subtotals, averaged by groupings, copy and paste to output tables; output tables = data source
conditional calculation: sumif/averageif function pivot table: report, chart |
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data model
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how data is organized, represented, accessed
efficient and effective org. of data: principles tempered by requirements of excel based DSS |
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database
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collection of tables that organize and store related information
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table
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lists of rows and columns containing info. on a subject
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columns
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field or attributes on subjects
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rows
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instances for each attribute
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data design principles
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minimize redundancy -- duplicate info. wastes space, increases likelihood of errors
efficient use of storage space and processing capability ensure correct and complete info. -- analysis based on incorrect data leads to bad decisions |
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good database design
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info. divided into subject based tables to reduce redundancy
tables can be linked together to retrieve data accuracy and integrity of info. data model of ind. analysis and processing requirements |
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DBMS design process
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purpose: range of expected uses
sources: identify and collect required data divide info. into tables: each major entity becomes a seperate table define columns/fields for each table: info. attributes assoc. with each entity/subject set-up table relationships: common fields link records across tables |
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DBMS vs. excel DSS
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DBMS: linked tables consolidated through queries; field structure based on subject attribute relationships apparent in the data
excel DSS: fewer tables; info. compared in single table; field structure based on analysis reqs. for grouping and filtering; excel influence data model design |
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growth issues
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tend to either grow or decline
steady state declining relative to competitors that are growing investors reward growth growth masks mistakes |
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mkt. share issues
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econ. of scale advantage
brand recognition - go with best leverage with suppliers correlated with LT profitability |
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calculation method -- pivot table
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convert growth/mkt. share data to excel table
select field by groups, categories, brands select data fields - growth rate, mkt. share, sales change fields and views for what if analysis refresh tables to look at updated data |
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quadrant charts
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plot growth-mkt. share results as quadrant bubble charts
purpose: facilitate interpretation through visualization; 4 quads. = benchmarks to eval. results |
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quad. chart midpoint selection criteria
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choose midpts. for x and y axis that yield most meaningful comparison of the bubble positions in the chart based on overall goal of analysis
look for benchmarks for x and y vars. that provide best context for comparison of data plotted choose measure broader than the data plotted - overall competitors - stores in chain as benchmark for store performance |
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product mix
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important factor in shopping choice
important in space constrained environment source of differentiation and competitive advantage |
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marketing mix elements
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price
promotion dist. product |
