Enterprise Business Processes and Applications (IS 6006) Masters in Business Information Systems 10 th Mar 2009 Fergal Carton Business Information Systems

Last week Apple fulfilment process and ERP impact –View by stage in the process (Requirement, Sales Order, Distribution, Invoicing, CS) –And by type of product –Where is commonality in process? –Where could ERP provide support? –Where would an interface be required?

This week CRM implementations eCRM ERP and reporting Decision support Compare plan to actual Data cubes Types of data Data collection

ERP impact for Apple All sales orders have to go through SAP Non SO-revenue must be interfaced –On-line sales –SAP interface for e-Commerce? Reporting of revenue ≠ collection of cash Universal Product coding, pricing Systems infrastructure requirements Support requirements

Integration is a trade-off Implementation of SAP in every sales outlet expensive? Control means knowing where inventory is Supply network is complex Visibility may be limited in certain regions Implementation and support resources

Why CRM Fails Why Does CRM Fail? –Disparate views of customers –Silo effect –Many types of CRM –Many types of CRM application

CRM is more than Technology Strategy important too Integrated business model needed Holistic view of customers needed Need to combine data from various sources Need to integrate value chain

Channel Disparity What sort of channels can a customer use to interact with a company? What sort of channel conflicts arise? Why do channel conflicts arise? What are the consequences for the customer? What are the consequences for the firm?

Operational and Analytical Disparity Data from Operations is not analysed – it gets buried in silos Business insights from Analytics are not applied to enhance operations Businesses tend to collect huge amounts of data –But little of use is done with these data

eCRM eCRM is an evolution of CRM using Internet technology A lot of eCRM is based around the customer portal A portal is a website that aggregates all of the customer’s shopping, research and service needs –E.g. amazon.com

eCRM and Portals Features –Online catalogues –Online order processing –Online order configurability –Lead capture and profiling –Online surveys –Literature fulfillment – (!) marketing

eCRM and Portals Advantages for customer –Customer is in control of purchasing process –Customer is not pressed for time –Site can be tailored to customer’s needs and interests –Customer can check out problems themselves

eCRM and Portals Advantages for company –Marketing information easy to gather –Profile of customer can be built –Cheaper than lots of call centre staff and physical retail locations

Families of Information Systems IS can be regarded as an umbrella name for the following systems: –Transaction Processing Systems (eg. ERP) –Reporting tools (eg. Data Warehouse) –Decision Support Systems (eg. Business Intelligence)

ERP Reports Based on hard reports – lists of transactions Originally targeted at middle managers each report took too long to create (hard coded); information was not refined enough; there was too much of it Not flexible Onerous in terms of processing

Different types of report exist: Scheduled reports (produced periodically) Exception reports (produced when something unusual happens) Demand (ad-hoc) reports (specific reports requested by a user) ERP Reports

Decision Support Systems set of tools provided to managers to assist them in solving problems in their own, personalised way. not all data computer generated support manager as opposed to replace them originally targeted at top managers interactive and flexible

What is a Decision?

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

Decisions compare plan to actual Compare –Plan to –Actual figure Decide on course of action

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

Example of data cubes

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 …

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...

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

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

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

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?