IS Consulting Process (IS 6005)

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IS Consulting Process (IS 6005)

• Masters in Business Information Systems
• 2009 / 2010

Fergal Carton Business Information Systems
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Last week

• UCC integration framework
• PCB exercise
• Analysis method, importance for budgeting
• Structure of requirements spec
• Families of IS
• TPS, Reporting, DSS and dashboards
• A framework for integration
• Dashboards from data to decisions

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This week

• UCC integration framework
• PCB exercise
• Analysis method, importance for budgeting
• Structure of requirements spec
• Dashboard design
• Data cubes
• Types of data
• Data recording,
• A framework for transition of data to decisions
• Dashboards Good Food Limited

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Integration framework for Uni (1)
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Integration framework for Uni (2)
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Proposal structure - example

• Executive summary
• Your understanding of our requirements
• Your recommended approach to undertaking this
  initiative including high-level project phases,
  key milestones and challenges which must be
  overcome
• Key personnel including brief biographies
• Project costs and any relevant terms and
  conditions
• Profile of the organization, including
• Overall consultancy services methodology
• Key consultancy offers
• Client portfolio
• Suitability for this contract, including details
  of similar engagements previously carried out

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A vendor proposal evaluation
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The nature of office work

• decision making (managerial level)
• data manipulation (preparing lists, meetings,
  agendas...)
• document handling (letters, memos, budgets...)
• communication (attending meetings, telephone...)
• storage (recording, storing and filing documents,
  archiving...)

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Decisions compare plan to actual

• Compare
• Plan
• to
• Actual figure
• Decide on course of action

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What is a Decision?
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Decision Support Systems

• set of tools provided to managers to assist them
  in solving problems in their own, personalised
  way.
• not necessarily totally computer-based
• support manager as opposed to replace them
• originally targeted at top managers
• interactive and flexible

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Dashboards from data to decisions
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Data for monitoring activities

• Norm or budget is put together
• based on experience, gut feeling or statistical
  analysis
• corresponds to expected levels
• the more complete the model the more complete the
  monitoring
• measurement methods and procedures are also put
  together
• the structure of the budget tells you what data
  to collect

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Example sales figures

• Sales dashboard is a key tool
• Allocate responsibility for poor performance with
  more accuracy
• Break down per product / market
• Present both volumes, gross revenues and
  contribution figures
• Use colour coding to indicate where results are
  good or bad
• Use sales maps for visual impact
• Comparison with
• Budget figures (e.g. weekly figures)
• Competitors
• Previous period
• Same period previous year in case of seasonality

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Example of data cubes
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Types of data 1

• Volume data (production)
• consumption data (raw material, packaging)
• personnel data
• maintenance data
• time related measurements
• productivity data
• All form the basis of the calculations used to
  monitor manufacturing activities

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Type of data 2

• Primary data
• taken straight from the floor (input and output)
• e.g. production, consumption, labour, maintenance
• ad-hoc reports - e.g. accidents, defects
• Secondary data or calculated data
• allocated costs
• productivity
• pay bonuses
• variances
• High level data
• investigations of variances
• soft information about staff morale etc...

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Type of data soft information

• Data collection -
• Grapevine
• factory tours (talking and observing)
• Data storage -
• managers minds
• special reports
• Data usage
• ad-hoc basis
• decision making

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Bad data recording

• No data!
• Too costly - e.g. in equipment or time
• not timely - lack of speed (e.g. weekly measure)
• inaccurate (e.g. procedure not well designed)
• wrong incentive / instructions given
• lack of control - open to dishonesty

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Data storage

• Series of ad-hoc systems manual and
  computer-based (spreadsheet, filed forms)
• Dedicated databases for manufacturing data (QC,
  shipping etc)
• Process Control Systems (technical parameters)
• Other specialised proprietary systems
  (integration may not be easy).
• ERP system with its own data structure or fed by
  existing systems

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Deciding what information to collect

• Information cost overload mean not all data are
  useful
• Some framework can be used e.g. Critical
  Success Factors (CSF)
• Questions that must be answered
• How is it measured and broken down?
• How often should it be measured?
• Who should know about it?
• Where can the data be found?
• How should it be presented?