SCM Dashboard

SCM Dashboard

5f2dd579b51fa5d5f5c09242407a9d8a?s=128

Vikas Luthra

May 22, 2013
Tweet

Transcript

  1. 1.

    Supply Chain Management Dashboard for Master Planners DD 312: Systems

    Approach to Design Guide: Prof. Pradeep G. Yammiyavar Co-ordinator: Asst. Prof. Abhinash Kumar Swain Client: JDA Software Team: Aditi Padhi – 10020504 Apurva Gupta – 10020509 Vikas Luthra - 10020544
  2. 2.

    Overview Introduction About the client Client brief Design brief Timeline

    Literature Review Supply chain management Existing scenarios/Dashboards Data visualization in cartography Methodology User research Mind map Story board User personas Use-case
  3. 3.

    Overview Result Information heirarchy A nity diagram Task ow Wireframes

    UI Designs Conclusion User testing Future works
  4. 5.

    Introduction About the client JDA Software is a leader in

    global supply chain management, o ering a broad portfolio of inte- grated planning and execution solutions and ser- vices to help rms manage the entire supply chain — from raw materials to nished products and into customers’ hands.
  5. 6.

    Introduction Client brief 1. Mockups/Wireframes The wireframes of the dashboard

    should be user- friendly and operable with as less e ort as possible. Key Performance Indicators (KPIs) should be shown intuitively. Planners should be able to drill down into the de- tails.
  6. 7.

    Introduction Client brief 2. Visualization of Data Supply chain data

    should be shown at di erent levels of detail. Visualization of data should be di erent for di erent planners. Content should be seamlessly integrated on di er- ent devices.
  7. 8.

    Introduction Client brief 2. Visualization of Data Supply chain data

    should be shown at di erent levels of detail. Visualization of data should be di erent for di erent planners. Content should be seamlessly integrated on di er- ent devices. 3. Audit of Existing Dashboards A view-point, as to where JDA’s report stands on the benchmarking index, should be provided.
  8. 9.

    Introduction Design brief Our aim is to design and evaluate

    an application package for supply chain management for master planners seamlessly integrated for both desktops and other portable devices.
  9. 10.

    Introduction Design brief Our aim is to design and evaluate

    an application package for supply chain management for master planners seamlessly integrated for both desktops and other portable devices. Planners are key personnel who analyze the data available to them to draft out future plans and business strategies. Thus, based on the roles, re- sponsibilities and tasks of the planners, the objec- tive of the project was to showcase the role spe- ci c data,i.e performance based indexes (KPI’s), trends, alerts/warnings, deadlines, etc. on a col- laborative DASHBOARD to aid planners to make informed decisions.
  10. 11.

    Introduction Timeline Research (Primary + Secondary) 25th Feb-11th March Analysis

    (Story-boarding) 11 March-18 March Ideation (Mind Map, IA, Persona, Use-cases, Task ows) 18 March-1 April Mockups/Wireframes 1 April-15 April Prototype 15 Apr-25 Apr Usability testing
  11. 13.

    Literature review Supply chain management Supply chain management is a

    network of facilities and distribution options that performs the func- tions of procurement of materials, transformation of these materials into intermediate and nished products, and the distribution of these nished products to customers.
  12. 14.

    Literature review Supply chain management Supply chain management is a

    network of facilities and distribution options that performs the func- tions of procurement of materials, transformation of these materials into intermediate and nished products, and the distribution of these nished products to customers. Supply chain activities cover everything from prod- uct development, sourcing, production, and logis- tics, as well as the information systems needed to coordinate these activities. Supply chain manage- ment, as mentioned before, is the active manage- ment of supply chain activities to maximize cus- tomer value and achieve a sustainable competitive advantage.
  13. 15.

    Literature review Supply chain management S u p p l

    y M a r k e t C u s t o m e r M a r k e t Control Decisions & Processes Supply Management Manufacturing Management Customer Demand Management Procurement Planning Production Planning Demand Planning Material Flow Information Flow
  14. 16.

    Literature review Supply chain management 1. Major decisions in SCM

    can be: Strategic(longer time horizon) Operational(daily basis)
  15. 17.

    Literature review Supply chain management 1. Major decisions in SCM

    can be: Strategic(longer time horizon) Operational(daily basis) 2. SCM decisions are spread over: Location Production Inventory Transportation
  16. 18.

    Literature review Supply chain management 1. Major decisions in SCM

    can be: Strategic(longer time horizon) Operational(daily basis) 2. SCM decisions are spread over: Location Production Inventory Transportation 3. Problems in SCM pertain to: Distrbution network con guration Distribution strategy Trade-o s in logistical activities Information Inventory management Cash- ow
  17. 19.

    Literature review Existing scenarios/ Dashboards A dashboard is an easy

    to read, often single page, real-time user interface, showing a graphical pres- entation of the current status (snapshot) and his- torical trends of an organization’s KPIs to enable instantaneous and informed decisions to be made at a glance. In other words,
  18. 20.

    Literature review Existing scenarios/ Dashboards A dashboard is an easy

    to read, often single page, real-time user interface, showing a graphical pres- entation of the current status (snapshot) and his- torical trends of an organization’s KPIs to enable instantaneous and informed decisions to be made at a glance. In other words, Data Decision Action
  19. 21.

    Literature review Existing scenarios/ Dashboards A dashboard is an easy

    to read, often single page, real-time user interface, showing a graphical pres- entation of the current status (snapshot) and his- torical trends of an organization’s KPIs to enable instantaneous and informed decisions to be made at a glance. In other words,
  20. 22.
  21. 23.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    1. It should o er the user with a choice of views. 2. It should use commonly accepted symbols and colors organization.
  22. 24.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    1. It should o er the user with a choice of views. 2. It should use commonly accepted symbols and colors organization. 3. Clear dashboard navigation and hierarchies should be established.
  23. 25.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    1. It should o er the user with a choice of views. 2. It should use commonly accepted symbols and colors organization. 3. Clear dashboard navigation and hierarchies should be established. 4. Dashboard groups should be used to improve organization.
  24. 26.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    1. It should o er the user with a choice of views. 2. It should use commonly accepted symbols and colors organization. 3. Clear dashboard navigation and hierarchies should be established. 4. Dashboard groups should be used to improve organization. 5. Actual values, percentages and trends should be represented.
  25. 27.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    1. It should o er the user with a choice of views. 2. It should use commonly accepted symbols and colors organization. 3. Clear dashboard navigation and hierarchies should be established. 4. Dashboard groups should be used to improve organization. 5. Actual values, percentages and trends should be represented. 6. It should use timestamps.
  26. 28.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    1. It should o er the user with a choice of views. 2. It should use commonly accepted symbols and colors organization. 3. Clear dashboard navigation and hierarchies should be established. 4. Dashboard groups should be used to improve organization. 5. Actual values, percentages and trends should be represented. 6. It should use timestamps. 7. It should use appropriate titles and labels.
  27. 30.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    8. Mouse-overs should be aptly utilized. 9. It should represent parameter-based views.
  28. 31.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    8. Mouse-overs should be aptly utilized. 9. It should represent parameter-based views. 10. It should use thresholds and threshold-triggered actions.
  29. 32.

    Literature review Existing scenarios/ Dashboards Usability issues of a dashboard:

    8. Mouse-overs should be aptly utilized. 9. It should represent parameter-based views. 10. It should use thresholds and threshold-triggered actions. 11. It should provide the user with the option of roll-ups and drill-downs.
  30. 33.

    Literature review Existing scenarios/ Dashboards Needs to be ful lled

    by a dashboard: Needs Organisational Business User IT Visibility Alignment Collaboration Intuitive Personalized Powerful interactive insight Rapid deployment Leverage Existing infrastructure
  31. 34.

    Literature review Data visualization in cartography Data visualization is the

    study of the visual repre- sentation of data, meaning information that has been abstracted in some schematic form, includ- ing attributes or variables for the units of informa- tion.
  32. 35.

    Literature review Data visualization in cartography Data visualization is the

    study of the visual repre- sentation of data, meaning information that has been abstracted in some schematic form, includ- ing attributes or variables for the units of informa- tion.
  33. 37.

    Literature review Data visualization in cartography Cartographic principles: 1. Legibility,

    i.e ‘the ability to be seen and under- stood’ 2. Visual contrast, i.e how map features and page elements contrast with each other and their back- ground
  34. 38.

    Literature review Data visualization in cartography Cartographic principles: 1. Legibility,

    i.e ‘the ability to be seen and under- stood’ 2. Visual contrast, i.e how map features and page elements contrast with each other and their back- ground 3. Figure-ground organization, i.e the spontaneous separation of the gure in the foreground from an amorphous background
  35. 39.

    Literature review Data visualization in cartography Cartographic principles: 1. Legibility,

    i.e ‘the ability to be seen and under- stood’ 2. Visual contrast, i.e how map features and page elements contrast with each other and their back- ground 3. Figure-ground organization, i.e the spontaneous separation of the gure in the foreground from an amorphous background 4. Hierarchical organization, i.e to separate mean- ingful characteristics and to portray likeness, di er- ences and interrelationships
  36. 40.

    Literature review Data visualization in cartography Cartographic principles: 1. Legibility,

    i.e ‘the ability to be seen and under- stood’ 2. Visual contrast, i.e how map features and page elements contrast with each other and their back- ground 3. Figure-ground organization, i.e the spontaneous separation of the gure in the foreground from an amorphous background 4. Hierarchical organization, i.e to separate mean- ingful characteristics and to portray likeness, di er- ences and interrelationships 5. Balance, i.e the organization of the map and other elements on it
  37. 42.

    Methodology User research Planners need to constantly take care of

    the fol- lowing information- facility pro les on map, scal calendar, my scorecard.
  38. 45.
  39. 46.

    Methodology User research Break-up of a master planner’s responsibilities: 1.

    20-30% time is spent on supply-demand match plan. 2. 30-60% time is spent on exception manage- ment.
  40. 47.

    Methodology User research Break-up of a master planner’s responsibilities: 1.

    20-30% time is spent on supply-demand match plan. 2. 30-60% time is spent on exception manage- ment. 3. 10-20% time is spent on performance manage- ment.
  41. 48.

    Methodology User research Break-up of a master planner’s responsibilities: 1.

    20-30% time is spent on supply-demand match plan. 2. 30-60% time is spent on exception manage- ment. 3. 10-20% time is spent on performance manage- ment. 4. 10-20% time is spent on improvement projects.
  42. 50.

    Methodology User research Key features of planning: 1. Planning runs

    2-3 times in a week, on an aver- age. 2. Before planning runs, data readiness for the next plan is reviewed.
  43. 51.

    Methodology User research Key features of planning: 1. Planning runs

    2-3 times in a week, on an aver- age. 2. Before planning runs, data readiness for the next plan is reviewed. 3. After planning runs, the plan is reviewed and approved, and then discussed with stakeholders.
  44. 54.

    Methodology User research Heirarchy of planners: 1. Planning Director /

    VP 2. Master Planner- Reports to VP 3. Facility Planner- May report to both VP and manufacturing operations
  45. 55.

    Methodology User research Heirarchy of planners: 1. Planning Director /

    VP 2. Master Planner- Reports to VP 3. Facility Planner- May report to both VP and manufacturing operations 4. Distribution Planner- May report to VP
  46. 56.

    Methodology User research Heirarchy of planners: 1. Planning Director /

    VP 2. Master Planner- Reports to VP 3. Facility Planner- May report to both VP and manufacturing operations 4. Distribution Planner- May report to VP 5. Business Operations- Owns a set of products and is responsible for programs around those products
  47. 57.

    Methodology User research Heirarchy of planners: 1. Planning Director /

    VP 2. Master Planner- Reports to VP 3. Facility Planner- May report to both VP and manufacturing operations 4. Distribution Planner- May report to VP 5. Business Operations- Owns a set of products and is responsible for programs around those products 6. SCM IT Analyst
  48. 58.

    Methodology Mind map MASTER PLANNER Exceptions Favourites Watch-List Metrics Communication

    KPIs Production Procurement Shipping Customer Feedback Caapacity Excess Utilisation Supply Cost Fill Rate Backlog Revenue Margin DOI Supply Excess Production Cost Alerts E-mail Delinquency Phone Saftey Stock Violation Capacity Under-utilised Late Demand Short Demand Production Plan Track Orders Escalation Production Issues Customer Change Requests Place Orders Capacity Constraints Delay in Work Order Completion CSRs Factories Monthly Weekly Shop Floor Planners Resolve Delay Dialing for Wafers Previous Customer Orders? A ects? What? Where? Why? Likely Date? Parts? Open Slots? How?
  49. 62.

    Methodology User personas 1. Jim Roberts Works at MX Inc.,

    Michigan Master planner of wireless products business unit
  50. 63.

    Methodology User personas 1. Jim Roberts Works at MX Inc.,

    Michigan Master planner of wireless products business unit Starts his day by looking at responses to his inquiries
  51. 64.

    Methodology User personas Motivations: a. Production issues, i.e nalizing the

    produc tion plan for the in-house factories for next week, while simultaneously coordinating with the shop oor planner
  52. 65.

    Methodology User personas Motivations: a. Production issues, i.e nalizing the

    produc tion plan for the in-house factories for next week, while simultaneously coordinating with the shop oor planner b. Procurement issues, i.e coordinating with the procurements division to ensure the pur chase orders for the next month are placed on time
  53. 66.

    Methodology User personas Motivations: a. Production issues, i.e nalizing the

    produc tion plan for the in-house factories for next week, while simultaneously coordinating with the shop oor planner b. Procurement issues, i.e coordinating with the procurements division to ensure the pur chase orders for the next month are placed on time c. Customer issues, i.e con rming the root cause of customer order issues using various reports and initiates communication to the factories, central capacity planners, while keeping the customer service representa tives and the BU managers in the loop
  54. 68.

    Methodology User personas 2. Amy Master planner at Ace Semiconductors,

    Loveland, Colorado Handles shipment and tracking of customer orders
  55. 69.

    Methodology User personas 2. Amy Master planner at Ace Semiconductors,

    Loveland, Colorado Handles shipment and tracking of customer orders Starts o by reviewing the morning’s planning re- ports for the products she manages
  56. 70.

    Methodology User personas Looks at orders that are running late

    or orders that failed to be planned due to some issues or orders promises that were escalated to her for manual inter- vention
  57. 71.

    Methodology User personas Looks at orders that are running late

    or orders that failed to be planned due to some issues or orders promises that were escalated to her for manual inter- vention Looks through her email to catch up with what happened around the global supply chain over- night
  58. 72.

    Methodology User personas Looks at orders that are running late

    or orders that failed to be planned due to some issues or orders promises that were escalated to her for manual inter- vention Looks through her email to catch up with what happened around the global supply chain over- night Frequently does “dialing for wafers”
  59. 73.

    Methodology User personas Looks at orders that are running late

    or orders that failed to be planned due to some issues or orders promises that were escalated to her for manual inter- vention Looks through her email to catch up with what happened around the global supply chain over- night Frequently does “dialing for wafers” Monitors metrics(delinquency)
  60. 74.

    Methodology User personas Motivations: a. What orders are running late?

    Why? b. Where are the parts that support this order? c. Where are my parts held up? d. What is the remaining itinerary for delivering this order? e. When will the order likely ship? f. What interventions are available to resolve this delay? g. Where are available open slots in the supply chain that could be available for this order? h. Which other orders are trumping this one for material or capacity? i. What has been our recent track record serving this customer’s orders? j. Did the inventory move as expected through the facility? If not why?
  61. 75.

    Methodology Use-case Important points noted from the use case: 1.

    Look at exceptions for orders and then resolve them
  62. 76.

    Methodology Use-case Important points noted from the use case: 1.

    Look at exceptions for orders and then resolve them 2. New exceptions on top, followed by old excep- tions for all orders
  63. 77.

    Methodology Use-case Important points noted from the use case: 1.

    Look at exceptions for orders and then resolve them 2. New exceptions on top, followed by old excep- tions for all orders 3. Look at actual and projected status for all orders due in current month, previous month and next 2 months
  64. 78.

    Methodology Use-case Important points noted from the use case: 1.

    Look at exceptions for orders and then resolve them 2. New exceptions on top, followed by old excep- tions for all orders 3. Look at actual and projected status for all orders due in current month, previous month and next 2 months 4. Big picture view of all procurement exceptions in near and middle term sorted in order of customer tier and then magnitude
  65. 79.

    Methodology Use-case Important points noted from the use case: 1.

    Look at exceptions for orders and then resolve them 2. New exceptions on top, followed by old excep- tions for all orders 3. Look at actual and projected status for all orders due in current month, previous month and next 2 months 4. Big picture view of all procurement exceptions in near and middle term sorted in order of customer tier and then magnitude 5. Option for the master planner to set indications to follow up on speci c orders
  66. 80.
  67. 88.

    Result Information heirarchy Homepage Exceptions Assembly Line + Item List

    Reports Report Summary Product Summary Alerts Collaboration Filter Noti cation + Animation Report List KPI’s Watch List Item List Item Summary Resolution
  68. 100.
  69. 101.
  70. 102.
  71. 103.
  72. 104.

    Conclusion UI Designs As per the timeline mentioned, we are

    in the user testing phase. We are still in the process of coordi- nating with the client to arrange for the same. Though the designs have been nalized, we intend to de ne the testing protocol and get it approved by the client so as to carry the project forward.
  73. 105.

    Conclusion UI Designs As per the timeline mentioned, we are

    in the user testing phase. We are still in the process of coordi- nating with the client to arrange for the same. Though the designs have been nalized, we intend to de ne the testing protocol and get it approved by the client so as to carry the project forward. Through this project, we were able to get ac- quainted with the standards of the industry. It also helped us learn the di erent design principles that can be used to visualize huge chunks of data in a user-friendly manner. Future works include col- laborating with the client to carry out the testing phase.
  74. 106.

    References 1. Chris Hendrickson, Logistics and Transportation Research, Vol. 19B,

    No. 5, pp. 359-360, 1985 Pergamon Press Ltd. 2. Intelligent Transportation Systems Architectures (Artech House Intelligent Transportation Systems Library). Bob Mc- Queen and Judy McQueen. Artech House Publishers, 685 Canton Street, Norwood, MA 02062, USA, 1999. 467 pp. 3. Frederic Lasserre, Logistics and the Internet: transportation and location issues are crucial in the logistics chain, Journal of Transport Geography 12 (2004) 73–84. 4. Scott J. Mason, P. Mauricio Ribera, Jennifer A. Farris, Randall G. Kirk, Integrating the warehousing and transportation func- tions of the supply chain, Transportation Research Part E 39 (2003) 141–159. 5. Qiu hong Zhao, Shuang Chen, Stephen C.H. Leung, K.K. Lai, Integration of inventory and transportation decisions in a lo- gistics system, Transportation Research Part E 46 (2010) 913- 925. 6. Ali Abughoush, Applying Business Analysis Techniques to
  75. 107.

    Dashboard Implementations, In press. 7. Yung-yu Tseng, Wen Long Yue,

    Michael A P Taylor, The role of transportation in logistics chain, Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 1657 - 1672, 2005. 8. Jan Ola Strandhagen, Erlend Alfnes, Heidi Dreyer, Supply Chain Control Dashboards, In press. 9. Solomon Negash, Business Intelligence, Communications of the Association for Information Systems (Volume13, 2004) 177-195. 10. Sander van der Putten, Valentin Robu, Han La Poutré, Annemiek Jorritsma, Margo Gal, Automating Supply Chain Negotiations using Autonomous Agents: a Case Study in Transportation Logistics, In press. 11. Koen Pauwels, Tim Ambler, Bruce Clark, Pat LaPointe, David Reibstein, Bernd, Skiera, Berend Wierenga, Thorsten Wiesel, Dashboards & Marketing: Why, What, How and What Research is Needed?, In press. References
  76. 108.

    12. Ioannis Giannopoulos, Peter Kiefer, Martin Raubal, Ge- oGazemarks: Providing

    Gaze History for the Orientation on Small Display Maps, In press. 13. Rainer Simon, Bernhard Haslhofer, Werner Robitza, Seman- tically Augmented Annotations in Digitized Map Collections, In press. 14. Derek F. Reilly, Kori M. Inkpen, Map Morphing: Making Sense of Incongruent Maps, In press. 15. Maneesh Agrawala, Chris Stolte, Rendering E ective Route Maps: Improving Usability Through Generalization, In press. 16. Peter Kiefer, Ioannis Giannopoulos, Gaze Map Matching: Mapping Eye Tracking Data to Geographic Vector Features, In press. 17. Dave Pegg, Design Issues with 3d Maps and the Need for 3d Cartographic Design Principles, In press. 18. White papers from Infosys, Coca-Cola Enterprises, IBM, ISB, Cognizant, Pureshare, CITO Research, Epicor, Ontonix References