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One of the things I enjoy most in process analysis is combining technologies. The idea is that deliverables generated by one technology, can be associated nicely with deliverables generated by other technologies. Such combinations reveal new magnificent insights about our processes, and opportunities for improving them. The three technologies that I find extremely friendly and "opened minded" for such a challenge are: the BPM manager of Priority ERP, Disco - an Automatic Process Discovery tool, and QlikView -a business discovery tool. The attached presentation includes practical examples to get you inspired. So, go ahead and give it a try!
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Mind Your Processes
Click, View & Do!
The Common Performance Measurement
Companies usually measure their performance in terms of financial data such as revenue, profits, cash flow, etc.
A common sales management dashboard
The Influence of Process Performance
The financial indices reflect the results of operational activities derived from the organization’s standard business processes
Addressing financial data only, without considering current business processes, significantly impairs an organization’s ability to improve their business performance
Process Minding
Most Business Intelligence (BI) solutions don’t provide insight into underlying business
processes In order to gain operational insights managers need:
► An integrated view of the company’s performance from process perspectives
► Real-time process monitoring based on operational KPIs (e.g., time, cost, quality, risk)
► Discovery of root causes of deviations from the planned process
Process Performance
Business Performance
The Solution
Automatic process discovery (APD): looks at historical event log data and analyzes these data to generate visual models of an organization's business processes
Advanced business discovery technology: allows management to analyze & monitor operations and key performance indicators in real-time and alerts management of any anomalies
Mind your Sales
Business Discovery with QlikView (BI)
The Business Discovery dashboard displays data & metrics based on sales data from the ERP system
The sales manager is not satisfied with the financial results in some countries There is also an increasing number of complaints from customers about delayed supplies The manager wishes to analyze operational data in order to learn more about the way sales
orders are handled.
Measuring Operational Performance
Operational KPIs are based on historical data of sales orders from the ERP.
The gauges bounds are defined by managers
Note: The dashboard is based on a gradual implementation. First, data for selected metrics
are retrieved in order to reveal performance issues with the process in question. Later on,
the gauges bound values are determined by the manager.
The Planned Process Model
The desired (As-Is) process flow is designed according to the process manager
The Process Model (in the ERP)
Built-In mechanism in the ERP is used to define and control process steps
The model includes statuses and paths between them - i.e., the workflow
Currently, there is no way to discover inefficiency or bottlenecks with reports generated by
the ERP.
How Events are Created
The sales Orders data are recorded in the ERP system
When updating a status or an employee in a sales order, an event record is created in a
sub-level screen
The event log data, together with business data can be retrieved from the ERP database for
the process analysis.
Process Discovery with QlikView
The Process Discovery sheet displays events & business data of closed sales orders from
the ERP
Analysis of process performance by various dimensions is enabled
Gauges display operational info about duration, efficiency, costs and more
The current sheet is linked to the Business Discovery sheet.
Analysis of Slow Orders (> 40 days)
Bar chart displays sales orders durations on the X-axis, and number of orders on the Y-axis
Pie chart displays costs and durations per statuses or employees
Gauges view is updated according to user selections
Business Data of the Slow Orders
The Business Discovery sheet is automatically updated with the previous selections
Only the slow orders-related data are displayed
Analysis of specific customers, part families or profit centers assists in discovering root
causes of issues in the process
Preparing Data for Automatic Process Discovery
Further analysis of the slow process can be performed with automatic process discovery
tool (e.g., Disco)
Data of the slow process can be selected & exported with a click of a button.
The Data Exported from QlikView
The mandatory data for automatic process discovery
Importing the Data to Disco
The Model of the Actual Process
The actual process flow discovered based on the imported process data
An Indication of inefficiency Start point
End point
Animation of the Slow Process
Sales orders starting the process
An Indication of a Bottle Neck
An Indication of work loads
Event Time
The actual process is replayed based on the imported process data
Analyzing the Fast Orders for Benchmarking
The chart displays now data of sales orders with a duration of up to 15 days.
Comparing slow & fast processing of the sales orders can reveal opportunities for
improvements (e.g., discover the efficient employees and adapt best practices)
The data is exported for further analysis with process mining technology.
Process Benchmarking
Fast Process Slow Process
Real-Time Process Control
The Process Control dashboard displays both business & operational data of open sales
orders
A deviation of case durations can trigger an alert (online or Email).
Mind your Production
An Overview of the Solution
The solution enables the analysis of the performance on a production floor and it’s
production process It is possible to analyze overall production performance and individual machine performance
across a number of key dimensions such as Work Center, Part, Time etc. Automatic process discovery can be performed on selected data to identify root causes of
deviations in costs, scrap, work orders cycle times and more This demonstration is based on sample of production reporting and cost data of work cells,
operations, products and machines from a metal processing company.
Manufacturing Analysis
with QlikView*
* Based on the Plant Operations demo app
The Dashboard
The Dashboard enables analysis of the high level KPIs: Costs, Scrap and Runtime Completed and Open work orders KPIs are displayed separately The data can be further analyzed by using the list boxes on the left of the sheet and the
time dimensions at the top.
Analysis of Costs
The Cost sheet lets you analyze the costs of the plant & its operations. With the charts in the container object, you can analyze Material, Overhead and Labor costs
and Actual vs. Standard costs for various dimensions (Work Center, Operation and Part). You can drill-down to focus on work order or operations with costs deviations
Analysis of Scrap
In the Scrap sheet scrap is displayed as a percent of production Scrap can be analyzed over time and by key dimensions
Discovering the Actual Production Process
With
Disco
Example Deliverables
The Planned Production Process
Some Possible Deliverables
A process map of the executed production processes Conformance Checking
► Deviations from routings
Performance Analysis ► Machines
► Operators
► Idle times
► Bottlenecks
Focused analysis of: ► Breakdowns
► Rework
► Rejected parts
Comparison of workers performance
Export Production Data for Automatic Process Discovery
Automatic process discovery can be performed on selected data to identify root causes of deviations in costs, scrap, work orders cycle times and more
The data imported from QlikView with a click of a button.
Revealing Deviations from Routing
For some work orders, the process starts and ends with different operations then defined in the routing (circled in red)
Start point
End point
Locating the Slow Work Orders
The Performance filter is used to retrieve slow work orders by a selected duration
The Slow Process Flow
The mean waiting time between operations
The mean duration of operations
Idle Times in the Process
The numbers represent the maximal waiting time between work cells
Mind your Warehouse
Warehouse Management System
Ordering & Receiving Goods to the Warehouse
Operational & Business Rules
Document Creation
Inventory Control & Quality
Assurance
WMS
WMS Terminology
Wave – Loop through a set of documents and create optimized tasks for picking, put away etc.,
taking under consideration resources, space, volume and other relevant parameters.
Task – A result of a wave that has a set of instructions that enables data entry with time tracking
and online error reporting.
Storage Zone – Physical or virtual storage space in the warehouse like front storage, back storage
or a gallery.
Warehouse Definitions (in Priority ERP)
Warehouse Tasks Details (in Priority ERP)
No. of open tasks for each user
PDA UI Forklift PDA or Laptop UI
Hand Held Device UI
PDA Pick sample
Pick recommendation
Pack Details
Show alternate Bins
Data entry Zone
Next/Previous Record
Copy Record Details
PDA Pick Example
WMS BI Dashboard in Priority ERP
WMS Analysis & Control
with QlikView
Current State of Warehouses
Throughput Analysis
Analysis of Mobile Devices
Analysis of Tasks Duration
Analyzing Warehouse Tasks
with Disco
Example Deliverables
Mind the Gap..
The planned process
The process in reality
PIK Tasks Distribution Among Storekeepers
The number of tasks allocated to a storekeeper
Comparing Storekeepers Performance
The numbers indicate the mean duration of paths between statuses
Task Types Comparison - Performance
Summary
Process Minding solutions can be applied to any system which manages processes
The solution can be developed with any BI tool
Some benefits of integrating automatic process discovery (APD) & BI technologies:
Holistic approach vs. detached (i.e., a stand-alone solution/service)
Event data are extracted directly from the BI database
Event data are enriched with business data
► Analysis and benchmarking results enable fine-tuning of KPIs
► Operational & business managers can share results and insights
► Continuous process improvement
More info & examples can be found here.
Contact Details
For further info please contact:
Dafna Levy
Email: [email protected]
Phone: +972 (0)54-6881739
Intelligent Process Management