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Business and IS Performance (IS 6010) MBS BIS 2010 / 2011 14 th October 2010 Fergal Carton (f.carton@ucc.ie) Accounting Finance and Information Systems
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Last week 1 Credit Suisse performance parameters –Return on investment (customer), bonus (fund manager) –What would be considered reasonable ROI from a customer perspective? Is this the same for a fund manager? –Return is related to level of risk taken –Overall corporate performance objective is broken down into sub-objectives for managers –This process of splitting objectives to individual managers is what Mason and Swanson (1979) are investigating Feedback on Mason and Swanson (CMR, 1979) –Scientific Measurement not enough for management decision support (softer information required) –Not “user specific“ –Metrics depend on your position (manager, customer, shareholder, employee, …)
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Last week 2 Managers have to make decisions regarding solutions to performance issues –These decisions necessarily engage the resources of the firm –Measurement systems do not support this level of decision making Class exercise: mobile phone sales down 25% with respect to target for quarter, what kind of decisions required –Knowledge of overall market performance might explain poor performance –Change targets? Try telling your boss that! –Act on demand by using discounts, bundles, promotion, marketing –In any case solutions involve committing resources (money, people, …) –What type of information support would a manager require to make such decisions? Collaboration / conflict arises: Sales versus Finance view
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Last week 3 Apple reporting exercise –Steve Jobs about to report results –You are asked to provide gift card revenue figures for Cork Channels used to sell gift cards eg. HMV Denominations sold (pre-set values or user definable?) Do retailers pay for cards up front? At what point are Apple able to recognise revenue from sale? What is the impact for sales reporting? –Make up of actual spend of gift card by product not known –Inventory impact versus non-inventory?
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Apple sales process An increasing range of channels –Apple stores (eg. ATMac, Penrose Wharf) –Apple.com –Major accounts (Dixons, Curry’s, Fnac, HMV, Virgin, …) –Retailer (Tesco, O2 stores, Argos, …) –Indirect distributor (Russian market?) –… An increasing range of products –iTunes –iTunes gift cards –iPods –iTouch –Accessories for all media players and phones –Notebooks –Desktops –iPhones –Service –Software –…
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Co-ordination strategies Co-ordination consists of: –Protocols, tasks and decision mechanisms to achieve concerted action between interdependent units (Thompson, 1967) –Decomposing goals to activities (Malone & Crowston, 1990) –People, resources and systems (Hepp & Roman, 07) Two key co-ordination strategies: –Centralisation of decision making (purpose agenda) –Standardisation of process (efficiency agenda) Inherent tension between individual and organisation Strategies impact flexibility of organisation differently IT only provides means of co-ordination, not reason
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How can data be shared –Face to face –Hard copy –Soft copy or email –Interface between applications –Access to a shared database –…
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Virtualisation Virtualisation: capturing & storing data relating to changes in the physical environment in an information system A measure of the degree to which information systems can reflect business reality Pre-supposes a structure (database), as data captured is related to a logical entity
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Basic flows Finance Sales Manufacturing
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Basic flows Finance Sales Manufacturing
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Inventory = common denominator Finance Sales Manufacturing
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ERP integration: demand & supply Production Distribution Sales X X X
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Student Dashboard
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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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Production planning and forecast In theory, it’s simple –Sales forecast future demand for products –Production plan to meet forecast sales But, in real life, there are many contingencies: –Sales tend to be optimistic –Most businesses exhibit seasonality –Customers are unpredictable –Forecasts are based on average prices –Yield may be poor due to quality issues –…
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How managers do their work What is happening? Actual What should be happening? Plan What therefore would happen if? What-if? Adjust plan and/or change actual Manage
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Criteria for information sharing –Integrity –Timing of information exchange –Knowing information is up to date –Ownership of data –Accountability if information is incorrect, incomplete –Decision responsibility
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Why is “one truth” so hard? Eg. Up to date picture of revenue? –Easy bit: all product shipped to date –Hard bit: Spares, loaners, replacement machines, … Deduct any current credit notes Add any outstanding debts from previous invoices Apportion revenue from service contract (12 months) Allow for discount to be applied if paid on time Currency exchange rate fluctuations … … –Revenue recognition “rules”
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What does integration mean? Dearden 72 –As computer use expands, control is vital –Single group of experts design a completely integrated supersystem = absurd –Specialist expertise is functional by nature –Finance, logistics, sales = different expertise –Centralisation of control of systems = dangerous –Examine the interfaces Vizard 06 –Data used to be in disparate databases –Data now in databases, file systems, applications, … –“One truth” concerning the state of a business process –Interdependent business processes (eg. sales & service) –Meta-data structures –Enterprise Application Integration vs. BI tools
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Who benefits? Finance gain greater visibility Manufacturing? –Demand may be too unstable for MRP –Production planning needs more “nuance” –ERP is too literal –Much planning still done on Spreadsheets Sales: need of integration
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Integration downsides Response times Vulnerability: single point of failure Limitations on expansion Dependence on single vendor Flexibility to change system … Access to basic information is complicated
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Control objectives of integration undermined
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Integration framework ExecuteSchedule Measure Performance control SupplyDemand Resource visibility Physical Virtual Plan
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