A management information system ( MIS ) is a subset of the overall internal controls of a business covering the application of people, documents, technologies, and procedures to solve business problems such as costing a product, service or a business-wide strategy
Management information systems are distinct from regular information systems in that they are used to analyze other information systems applied in operational activities in the organization.
It has been described as, "MIS 'lives' in the space that intersects technology and business. MIS combines technology with business to get people the information they need to do their jobs better/faster/smarter.
Old MIS Systems
Generally a few summary reports and a few detailed reports grouped for a business function and menu having multiple such groups
No well thought of framework for organizing, automating and analyzing business methodologies, metrics, processes and systems that drive business performance
Difficult to figure out ‘cause and effect’ relationships
Manual detection of problem points from a group of detailed reports
Decision making more dependent on intuition
New Generation MIS Systems (also termed as performance management systems)
Based on a sound framework for organizing, automating and analyzing business methodologies, processes and systems that drive business performance.
Business processes are aligned with Strategies and KPIs are aligned with business processes
Status indicators (KPI) set with defined target and/or tolerance ranges
KPIs are published into a dashboard / scorecard with the ability to drill down to detailed analysis or trend reports.
IT landscape (hardware, software, application) grew too large
No enterprise-wide standard (process, information, IT)
Information is not ‘trusted’
Cross business function information gathering is dependent on huge manual effort & error prone
Some common issues faced by decision makers
Data is scattered everywhere across our organization. Where do I look ?
It takes forever to get the information I need to do my job
When I do get it, it’s wrong
We have mountains of data, but I can’t figure out what’s important
It takes so long to get the data that I don’t have any time left over to analyze it
I want it to be easy to see my data in every possible combination. Just let me point and click my way to an answer
I want a historical view of the business or make future projections
How can I plan based on the lessons learned and future projection
KPIs : selected measures of business performance Carefully selected set of measures derived from strategies, goals and objectives that represents a tool to communicating strategic direction to the organization for motivating change. These form the basis to plan, budget, structure the organization and to control results. Customer Measures % Sales of New Products Customers Acquired Customer Satisfaction Customer Retention Financial Measures Market Share % Revenue from New Products Transportation costs (costs/mile) R & D and Human Resource New Product Introduction Management Skills Employee Turnover Internal Process Measures Product Time to Market Unit Manufacturing Cost Days Supply to inventory % revenue from new products It is the ratio of money gained or lost (realized or unrealized) on the product relative to the amount of money invested on the same Customer retention rates Among the total customer, what are customers who are staying with the company after specific period of time. Its generally calculated yearly basis Customer satisfaction Customer satisfaction is a measure of how products and services supplied by a company meet or surpass customer expectation, for a particular service/product line. Generally estimated through survey and using a scoring model on a pre-defined scale.
Conceptual View of Enterprise Business Intelligence Executives Departments, Managers Touch Points- Customer, Vendor, Partner, Organization Units BI Real time BI, Embedded Analytics, Operational Dashboard Tactical BI Strategic BI Operational BI “ Capture” Distributed Operational Systems, External Data Providers, Unstructured Data Sources “ Collate” Centralized Information Warehouse “ Deliver” Distributed Analytic Applications Operate Plan Strategize Dashboards, Reporting, Analysis, Planning, Budgeting, Mining & Predictive Analysis Scorecards, Reporting, Planning, Budgeting, Performance Management
Logical View of Enterprise Business Intelligence LAN Vendor ENTERPRISE DWH BATCH Near Real Time REAL TIME DATA INTEGRATION REAL TIME OFFER OPTIMIZATION TOUCHPOINTS WRITE-BACK WRITE-BACK DYNAMIC SCORING & SEGMENTING REAL TIME CAMPAIGN MANAGEMENT REAL TIME OFFER SELECTION REVIEW SEGMENTATION/PRICING MODELING REAL TIME CAMPAIGN RESPONSE INTEGRATION REAL TIME SEGMENT MIGRATION DATA MANAGEMENT DW MANAGEMENT DISTRIBUTION MANAGEMENT PERSONALZATION & DELIVERY INFORMATION MANAGEMENT PROCESSES BATCH DATA INTEGRATION PORTAL UNSTRUCTURED DATA STORE
ERP or Custom implementations supporting operational need:
Sales & Marketing
Manual systems mainly either in skill areas or around niche business functions:
Planning & Budgeting
Sales Rep Incentive Calculations etc
Third Party Data:
Address & demographic data
Market research data etc.
ETL vs EAI Areas EAI ETL Definition Technology solution that enables systems to communicate Process designed by users to extract, transform, and load data from one or more sources to a target data repository Performance Optimization System is aimed at reducing the response time for a single user request or update System is aimed at reducing total time to create the unified historical record Integration Applications Data Focus Operational & Strategic Operational Business Case IT, e-business, Better Workflow, Data entry once Business Intelligence, Decision making, large volume, complex transformation, data quality Time Real Time Batch (moving to real time) Data Transactional-small Historical-enormous Metadata Limited--Message metadata Rich--dimensional metadata Transformations Format oriented --Code supported Analytic, Joins, Aggregations, function & formulae based Volume Single transactions Messages/second (KB) Days or weeks of data Records per min (GB) Targets OLTP API Code supported Relational Structures Native connectivity Codeless Extracts Data Using API’s Directly from database or using application adapters System Admin Involvement EAI requires no system administrator involvement. Once implemented, EAI is a technology solution that is transparent to end users. ETL requires extensive system administrator involvement ENTERPRISE BUS EXTRACT TRANSFORM LOAD Metadata ETL Transformation EDW
An operational data store (or " ODS ") is a database designed to integrate data from multiple sources to make analysis and reporting easier. An ODS is usually designed to contain low level or atomic (indivisible) data (such as transactions and prices) with limited history that is captured "real time" or "near real time“.
According to Bill Inmon , the originator of the concept, an ODS is "a subject-oriented, integrated, volatile, current-valued, detailed-only collection of data in support of an organization's need for up-to-the-second, operational, integrated, collective information."
In practice ODS tend to be more reflective of source structures in order to speed implementations and provide a truer representation of production data.
An " ODS " is not a replacement or substitute for an enterprise data warehouse but in turn could become a source.
Operational Data Store Data Warehouse Characteristics Data Focused Integration from Transaction Processing Systems, A better integrated picture of source systems Subject Oriented, Integrated, Non-Volatile, Time Variant Age Of The Data Current, Near Term (Today, LastWeek’s) Historic (Last Month, Qtrly, Five Years) Primary Use Day-To-Day Decisions, Tactical Reporting, Current Operational Results Long-Term Decisions, Strategic Reporting, Trend Detection Frequency Of Load Real Time, Near Real Time, Twice Daily , Daily, Weekly Daily, Weekly, Monthly, Quarterly, Bi-Yearly, Yearly
The barrier between transactional systems — which run the business day to day — and decision support — which traditionally have engaged business intelligence issues around product, customer, and market trends — is fading away under the pressure of new and ever more demanding business scenarios in customer service, product distribution, and market dynamics
A call center agent who has a customer on the phone at risk of going to the competition has 15 seconds to turn the situation around.
Analytics are used to optimize operations . For companies like FedEx, package dynamics are not just transactional; they are critical path — literally in a strategic and tactical sense — requiring the redeployment of resources such as aircraft to optimize operations.
Supplier scorecards — on-time deliveries, returns, defects, incomplete orders — reduce revenue losses from out-of-stock items and reduce markdown losses from overstocks.
For those enterprises that have physical inventory, reducing inventory through a demand planning or forecasting data warehouse results in significant cost reductions.
Data updates can only be as fast as the business processes that produce data.
Data consumption can only be as fast as the warehouse.
Right Latency is the right thing to implement Type Definition How it works Example Simulated An end user at a work station executing self-service query and reporting or what-if analysis. Updates and roll-up calculations are performed in batch, delivered in interactive “think time.” The results have been pre-computed and stored in the data warehouse for latter delivery as if the calculation were done in real time, but it is not. Customer recommendation Right time A catch-all phrase meaning near-real time — tied to a specific technology such as change data capture to a database log. Allows for a variety for response times, none committing to synchronous processing — allows for distribution by an ETL tool or message broker Web log analysis Real time The answer is absolutely the most up-to-date information physically possible in terms of both update and access. Resources such as databases, networks, and CPUs are locked synchronously until a commit point is reached, at which time other concurrent processing may proceed. Fraud detection On time Data is updated and delivered according to policies, service-level agreement, or consensus. Business groups tell IT how often they need to update and access data, and IT delivers data on that schedule. Inventory