# Which Supply Chain Planning platforms incorporate supplier lead time variability into replenishment recommendations?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">I'm researching which Supply Chain Planning platforms actually factor supplier lead time variability into replenishment recommendations, rather than assuming a fixed lead time that rarely matches reality. Inside <a class="a a--md" elv="true" href="https://www.g2.com/categories/supply-chain-planning">Supply Chain Planning</a>, <strong>Kinaxis</strong>, <strong>o9 Solutions</strong>, and <strong>Logility Solutions</strong> stand out for handling this specifically.</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/kinaxis/reviews"><strong>Kinaxis</strong></a>: built for concurrent planning that can react to lead time changes in near real time, useful when supplier variability is causing frequent replenishment misses.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/o9-solutions/reviews"><strong>o9 Solutions</strong></a>: uses probabilistic modeling that can account for variability rather than treating supplier lead times as a fixed number, which shows up directly in replenishment recommendations.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/logility-solutions/reviews"><strong>Logility Solutions</strong></a>: strong inventory optimization features that factor supply variability into safety stock and replenishment calculations.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/anaplan/reviews"><strong>Anaplan</strong></a>: flexible enough to build custom models around lead time variability, though it takes more setup work than platforms with this built in natively.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/oracle-demantra/reviews"><strong>Oracle Demantra</strong></a>: older but established demand and supply planning tool, with lead time considerations available though generally less dynamic than newer AI-driven platforms.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For supply chain teams dealing with genuinely unpredictable suppliers, did factoring in lead time variability actually reduce stockouts and overstock, or did the model still need manual overrides when suppliers really went off script?</p>

##### Post Metadata
- Posted at: 12 days ago
- Net upvotes: 1


## Comments
### Comment 1

Supply Chain Planning reviews on G2 treat lead time variability as a modeling choice with real tradeoffs, not a solved feature. o9&#39;s probabilistic modeling showing up directly in replenishment recommendations is a structurally different approach than Kinaxis&#39;s concurrent planning reacting to changes near real time; one is baking uncertainty into the forecast itself, while the other is responding faster once uncertainty resolves into an actual delay.
Logility folding variability into safety stock and replenishment calculations is a narrower, more specific claim than either of those, worth verifying it fits a team&#39;s actual product mix before assuming it generalizes. Anaplan&#39;s flexibility to build a custom variability model is a different kind of commitment than the others, since it trades a longer setup period for a model shaped exactly around a specific supplier base, which only pays off if that supplier base is unusual enough that an out-of-the-box model wouldn&#39;t fit anyway.


##### Comment Metadata
- Posted at: 10 days ago
- Author title: Marketing





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