How to Choose Supply Chain Planning Software: 6 Criteria

To choose supply chain planning software, judge each vendor on six things: how deep its optimization goes, whether it plans concurrently or one module at a time, how often planners accept its recommendations and whether it can explain them, how it connects to your systems, how quickly it reaches results, and what its references can show. Test those claims on your own data before you sign. If you are still deciding whether to replace spreadsheets at all, start with our post on supply chain planning in Excel.

What to Define Before You Compare Vendors

Write four things down first, or every demo will look good:

• The decisions you want the system to make: replenishment, allocation, purchasing, production, fulfillment, transport.
• The constraints those decisions must respect: pack sizes, minimum order quantities, lead times, shelf life, warehouse and truck capacity.
• The KPIs that should move, with their current values as a baseline.
• The systems the planning tool must read from and write back to.

Use them as the scoring sheet for every demo.

How to Choose Supply Chain Planning Software: The Six Criteria

Criterion	What to check
Optimization depth	Real constraints are modeled as hard limits, and the objective trades off cost and service
Concurrent planning	Inventory, production and transport are solved together, not in sequence
Acceptance and explainability	Share of recommendations executed with no planner edits, and a reason for each recommendation
Integration	Native ERP connectors, write-back of plans, no full data migration
Time to value	Weeks from contract to live decisions, and months to measured results
References	Named customers with results measured against a baseline

Optimization Depth and Concurrent Planning

Some planning tools forecast well and then apply rules to turn the forecast into orders. Rules break when constraints interact. Ask the vendor to show a plan for one of your categories and check whether it respects your pack sizes, lead times, shelf life and capacities without manual fixes. Ask what the engine optimizes: total cost to serve against a service target, or a single measure such as forecast error.

Then ask how the modules connect. A plan built one module at a time can look optimized in each module and still be infeasible as a whole: the inventory plan assumes production capacity that the production plan has already used, and the transport plan cannot move what both of them promised. Solvoyo calls this phantom feasibility. A concurrent engine solves inventory, production and transportation together, so the plan it hands to planners can execute.

Acceptance Rate and Explainability

A direct test of a planning system is how often planners run its recommendations without changing them. Solvoyo measures this as user acceptance rate (UAR), also called no touch rate: decisions executed exactly as recommended, divided by all decisions executed. Usage figures such as logins or recommendations generated only show that people opened the tool.

Ask each vendor:

• What is your acceptance rate per workflow, in named customers, and how is it calculated?
• Is every planner edit logged with a reason code?
• Can a planner see why the system chose a quantity, a source or a route?

Explanations also keep acceptance high after go-live. A planner who can see the reason behind a recommendation can tell whether an edit adds information the model lacks, and when it does, the model gets a new input.

Integration With Your Existing Systems

Planning software reads master data and transactions from your ERP, WMS and POS, and its value depends on writing plans back. Ask:

• Is there a native connector for your ERP, or only a file interface?
• Which methods are supported: web service APIs, direct database transfer, middleware, EDI, files?
• Does the ERP stay the system of record, or does the project need a full data migration?
• How are data gaps found and flagged during onboarding and after go-live?

Solvoyo, for example, connects to SAP through RFC and to other systems through REST or SOAP web services, database transfer and middleware, and its data diagnostics flag gaps at ingestion.

Time to Value and How to Test Before You Commit

Ask for two dates: when planners will work from live recommendations, and when the business KPIs will show a measured change. Solvoyo reaches a production-ready configuration in about 12 weeks, and customers typically see measurable results within three to four months.

A long RFP built around scripted demos tells you little about how the system handles your data. A funded Test and Learn on a limited scope, using your real workflows and data sources, shows data quality, integration and change-management issues before you commit to the full scope. We explain the reasoning in why RFI, RFQ and RFP processes do not fit SaaS purchases. Scenario and what-if capability deserves its own test as well; our post on what-if analysis in SCM software selection covers it.

References and Proof

Ask to speak with customers in your industry, at a similar scale, who run the workflows you plan to automate. Ask them three things: what the acceptance rate is today, which KPIs moved and against which baseline, and how long the vendor’s team stayed after go-live. Published case studies help when they name the customer, the scope and the measurement period.

Questions to Ask Supply Chain Planning Software Vendors

• Which of our constraints does your engine model as hard limits?
• Are inventory, production and transport planned in one solve or in sequence?
• What is your acceptance rate in named customers, per workflow?
• How does a planner see the reason for a recommendation?
• How do you connect to our ERP, and do plans write back automatically?
• What do you need from our team, and for how many weeks?
• When will we see live recommendations, and when measured results?
• Can we start with one function and add others later?

How Solvoyo Fits These Criteria

Solvoyo is a supply chain decision automation platform. One mixed-integer solve weighs cost, service, capacity and lead time together, and reason codes explain each recommendation in plain language. Because real constraints are modeled as hard limits and each recommendation carries its reason, over 95% of plans execute untouched, a rate Solvoyo tracks on every decision and publishes in named case studies.

The Technology page shows how the engine works, and the user acceptance rate page explains the measure. To score Solvoyo against your own criteria and data, request a demo.

Frequently Asked Questions