In my experience as an analyst, 70% of teams selecting supply chain software become polarized and dysfunctional. Why the melt-down?  It is simple.  Teams are not clear on what is required before they start the system selection process. 
I often find myself as an uwilling participant in the heat of a battle.  They can get very UGLY.  When this happens, teams call asking “should I select vendor X or Y?  Which is best?”  I don’t win many congeniality contests when I tell the team that they are asking the wrong question.   
This is more problematic now than three years ago. Consolidation, the evolution of new best of breed players and a TCO (Total Cost of Ownership) focus can pit departments against each other. Here we share some insights:  

• Consolidation.  The technology space has consolidated and 25% of manufacturing companies are looking to replace supply chain technologies to improve costs, integration or optimization.  There is no PERFECT solution.  To avoid dysfunction, teams should discuss the trade-offs up-front and agree on relative importance.   

• Gaps in Knowledge:  One of the issues leading to the problem is the current knowledge level of software technology providers.  As companies have been bought and sold, the aggregate knowledge of supply chain planning in the industry has declined.  We also find this to be true, due to focus on ERP implementations and a decrease in focus on planning, with consulting partners.  To help, the  Supply Chain Shaman has developed a list of questions to ask. 

Questions to Ask

Scalability.  There are several definitions of scalability –time to run a batch optimization plan, time for the user response, time to calculate what-if analysis, the time to run batch reporting– to focus on. How do you define scalability?

•  For a batch run? For what-if analysis? For multi-user environments? How do you run an optimization routine and continue to support global operations? (E.g. the batch windows have to be timed to roll across the world)  Can you live with the downtime?
• What technology capabilities are needed to improve the response?  Does the system have net-change logic?  Parallel processing?  Learning algorithms?
• Have you planned for regular optimization tune-ups?
• How do you synchronize demand to reduce demand translation?

 
Tactical Planning. Tactical supply chain planning is optimization to calculate the best plan for master planning (from the period of 1 month to 12 months). This capability is a pre-requisite for successful S&OP planning.

• What is required to model your environment?  At what level?  At multiple levels of the process?  
• Can the operation be modeled through heuristics?  (Many companies using simplistic models use heuristics at one level of the factory in an unconstrained model.)
• Do you have floating bottlenecks?  Vertical integration requirements?  Can the bottlenecks change across the envelope? Do you need to plan for shared resources? (tools, dies, etc)
• Do you need to model plants within plants?  What defines a resource and a manufacturing facility?
• What resources can be substituted?  How do you define an agile network?  Who makes this decision?  Outline what this flexible mapping looks like for the conference room pilots.
• How do you define the rules for agile manufacturing rules or alternate resources (e.g. if this plant is not available go to this plant).
• How do you manage make-to-order processes?  What is required? 
• Does the system need augmentation?  Do you need to add a multi-enterprise inventory planning system like IBM, Optiant, SmartOps or ToolsGroup? Do you need to use a system like Ortec to improve truck utilization? Do you need a system like Aspentech BDP to plan for bulk loading?
• How do you account for alternate formulations in the integration to MRP?   What is needed at a product data model level? What is needed from integration for process PLM? And System recipe management?  How do you connect formulation specifications to recipe management to site specifications?
• How do you model push-pull boundaries to determine the best postponement strategy?
• What is modeled and how are common materials modeled in the Bill of Material?  What are the requirements for dependent demand for kitting, display packs, etc?   Is reverse Bill of Material functionality required? How are grades, densities and other changes in material stream variance accounted for?
• What is needed to support Sales and Operations Planning (S&OP) processes?  What defines a good plan?
• How will you model for sustainability to know the impact of the plan on upcoming Carbon regulations?  How will you link profitability decision making to the plan?
• Is the tactical plan best served in a constrained or an unconstrained tactical plan? If constrained, define the constraint carefully.  Can the constraint be measured?  Does it float?  Is there more than one constraint?  After you constrain the plan, what are you going to do with the output?
• How do I design the instance strategy to yield the best output for supply chain visibility?

 
Planning master data. Long supply chains with variability in inputs have the greatest need for planning master data systems.  To determine if you need a master data system for planning, list all of the data inputs into the planning system.  Then ask yourself these questions:

• What data is important?  What is important and variable? 
• If data is important and variable, focus on building a planning master data layer to support supply chain planning.
• If the important and variable data is manufacturing data, build an information layer based on EMI (Enterprise Manufacturing Intelligence systems) into a planning master data base and plan using the probability of the value.  (E.g. if the standard run time is X and the actual run time has a standard deviation of Y use the range or account for the standard deviation)

 
What if analysis. What if analysis is the capability to determine what would happen if variables change using optimization logic.  To determine the requirements, consider:

• Define “what if analysis” requirements very carefully for each planning horizon and application considered.  In the definition of requirements, be clear on the impact on other users in multiple-use scenarios (E.g. is the data partitioned sufficiently that one planner can drive a what-if analysis on their data set and not cause an outage for other planners?)
• Focus on the conditions under which you will accept the what-if conditions for the new plan?  Determine the and the how.
• If you are determining the most feasible plan through event-based simulation, determine how you will you tie event-based simulation to what if optimization modeling?

 
Available to Promise (ATP).  ATP allows companies to more accurately promise order deliveries. Some key questions include: 

• How do you define Available to Promise (ATP)?
• Why is it important?  What are the integration points and the decision triggers?
• How do you reach the level of operational discipline to make it a reliable signal?
• How does the availability of ATP redefine order management?  Manufacturing scheduling?  Demand shaping?  Decisions across order types and channels?
• Do you have sufficient supply chain visibility to plan for materials in-transit?  Do you have the transportation reliability to consider in-transit finished product?  What is needed for integration?
• How do you collect data across multiple-enterprise manufacturing systems to ensure that it is a network signal (representative of tolling, outsourcing, suppliers, etc?)
• Does the ATP signal require integration into sell-side contract management to ensure the right application of terms and conditions?

 
Production Scheduling.  Factory scheduling is some of the most problematic software to select.  It is very industry-specific with a great range of solution variability.  Clarity is required in these areas:

• What makes a good plant schedule (e.g. return on assets, shorter change-overs, schedule adherence)?  And why?  How does this tie to the definition of supply chain excellence?
• How will you monitor and reward production schedule excellence?
• How frequently will you need to schedule the factories? Who will need to see and review the schedule changes? How often will you have to reschedule? What are the requirements for what if analysis?  (Be careful to set up the system so that when what if analysis is performed by one planner that there is no interference with the rest of the planners on the system)/
• What integration is required for supplier managed inventory and commodity management? How frequently and how tightly will the signals be interfaced?
• What is the role of Available to Promise (ATP) in scheduling?  Will the organization use planned production for calculating the ATP signal?
• How do you prioritize orders coming into manufacturing?  By customer and by product type?  Which orders will necessitate the need for a schedule change?
• What defines the most efficient campaign on a manufacturing line?  How do you continually refine this based on continuous improvement programs?
• What is needed in production planning to best manage third-party relationships? (drayage, third-party logistics providers providing materials, third-party quality relationships)
• How will the new Cap and Trade regulations change the desirable output of the factory scheduling models?  What needs to be monitored as inputs to monitor impact of the factory on the carbon footprint of products manufactured?
• Before contacting a technology provider, define routings, bottlenecks, shared resources and constraints for each level of manufacturing to be modeled.  After identifying these modeling parameters, answer the question:
• When do you have floating bottlenecks? How do floating bottlenecks change based on product mix and raw material variations? How many levels of production need to be modeled?
•  How many levels of production do you need to model to schedule for labor requirements? For ATP visibility?  To manage constraints?
• When are materials the constraint?  What interfaces are required to production materials planning (MRP)?
• When you share resources, how do your prioritize shared equipment, die sets and tools?
• How do you deal with hold, cure, and dwell times?
• How do you model processes that do not have reliable outcomes or production variability? (E.g. the output of a reactor, brix content in juice, etc.)

 So apologies to all the teams, that ever asked me the “question of should they chose vendor X or Y, and I asked the team to  go-back to the drawing board to define their requirements.”  For you see, the requirements do matter.  I will never win the Miss Congeniality contest. 
What do you think? Any questions to add to the list?