Data Insight • March 25, 2025

To Buy or To Build?

With the explosion of digital tools, buying or building tech solutions has become an even more pertinent question for supply chain leaders. We zoom in factors impacting the decision, then explore the question as it relates to AI agents.

Jalen Thibou Avatar
Jalen Thibou
Digital Strategy
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The Data

  1. 1

    Research shows that since 2020, companies have been buying more SAAS solutions in supply chain, with market revenues increasing by 200%.

  2. 2

    Companies like Walmart, Unilever, and IKEA are just some of the companies building internal technology teams and tech solutions for their supply chains.

  3. 3

    Zero100 analysis shows the logistics and manufacturing functions are leading on AI agent patents in supply chain, which we consider indicative of efforts to build this tech, responsible for 58.3% and 30.6%, respectively.

As supply chains continue through a post-pandemic era and a surge of AI-powered solutions, leaders looking to accelerate their businesses are dealing with the perennial question of buy vs build when it comes to tech. 

On one hand, reports show that companies are continuing to invest in SAAS providers, with market revenues increasing by 200% since the cash-conscious times of 2020. On the other hand, open-source solutions and the increase in supply chains forming and developing their own internal tech teams or fusion teams suggest that some are looking for the customization and flexibility that comes from building a solution.  

The Solution Depends on the Problem 

Start by assessing the capabilities you want to gain and asking why, lining up with bigger business goals and intended value. Both buying or building come with their own set of opportunities and challenges, some of which include:  

Table listing opportunities and challenges for buying and building technology.

Buying 

To help those looking to buy technology off the shelf, our data science team created a solutions provider capability database to help evaluate what solutions providers can do and how they leverage AI. 

As an example, let’s delve into contract lifecycle management (CLM). In The Zero100 AI Hub, CM has six sub-processes. We analyze and assess 70+ solution providers in the sourcing space to understand if they have a) CLM capability, b) which CLM subprocesses they support, and c) which of those sub-processes are AI-enabled. In the figure below, you'll see each sub-process and the percentage of providers that use AI. Using this model helps close the gap between your internal teams' capabilities and what solution providers are offering. 

Bar chart comparing AI capability for CLM, point solution provider vs end-to-end solution provider. Source: Zero100 Vendor Capability Database

Building... AI Agents 

With AI agents a hot development offering supply chains the ability to gain new levels of productivity and growth with automation, we analyzed patent data as an indicator of internal investment in building this new tech. We found this functional breakdown:  

Logistics: 58.3% 
Manufacturing: 30.6% 
Planning: 5.6% 
Sourcing:5.6% 

With major disruptions in recent years, plus the need to adapt to new network challenges with the rise of e-commerce and the necessity of omnichannel capabilities, it’s not surprising that logistics and manufacturing hold the majority of these patents in supply chain. 

In Action 

IKEA has built a new demand sensing tool that uses ML on top of data to optimize inventory deployment in its networks. It expanded its data lake, which now tracks 200 different data sources for each SKU. In the previous model, demand spikes in any particular store would be reflected across the whole region or country. Now, the demand sensing tool recognizes that a particular demand spike is localized, and IKEA is able to adjust inventory and orders at the local level. This tool is close to real-time and can predict up to four months in advance.  

VF Corporation is working with multiple solution providers, transitioning its supply chain to SAP S/4HANA as its transactional backbone, integrating Blue Yonder for planning and allocation, and using o9 Solutions for end-to-end supply chain planning. This unified system integrates demand signals and supply plans, covering the procurement of raw materials and finished goods with real-time visibility per segment. VF also utilizes Infor for production planning, Infor Nexus for supply chain visibility, and 3D applications for digital product creation, enhancing both speed to market and customer engagement through virtual product representations. 

The Takeaway 

Whether you are buying or building your own technology, define the problem and consider how it aligns with your long-term time horizon goals. Then, determine whether off-the-shelf tech or building a tailored solution is directly aligned to imperatives like scope, ROI, and capabilities.  

If you choose the former, evaluate the capabilities of existing SaaS providers to see if they match your required capabilities with a structured assessment – we can help with this. If you choose the latter, ensure you have the internal talent skills that will be necessary for a tech deployment team by upskilling current talent or hiring new talent with the right expertise. Then, lean into lessons from leaders already investing in their own proprietary technologies. 

Reach out to us at hello@zero100.com to learn more about our AI frameworks and the Zero100 AI Blueprint, which is how we help companies mold their data-centric supply chain strategies and prioritize AI investments. 

Methodology  

Zero100 ingests hundreds of thousands of patents from the world's largest companies and classifies them using AI.  

Zero100’s proprietary data and analytics are a combined effort between our data scientists and research analysts. We provide data-first insights matched with our own research-backed points of view and bring this analysis to life via real-world case examples being led by supply chain practitioners today.      

Further Reading