Why order automation projects fail (and how to run one that doesn't)

Order automation projects fail for the same reasons every IT project fails: nobody owns the outcome, success is never defined, decisions stall, and the people who have to change how they work were never brought along. The software is rarely the problem. In CIO's August 2026 feature "Why IT projects still fail", Mary K. Pratt collected 12 culprits from project consultants and CIOs. Not one of them is a technology defect. In its 2026 Pulse of the Profession report, the Project Management Institute found that 31 percent of complex projects fail to deliver the full scope of their intended benefits.

This post walks through all 12 causes and shows how a well-run order entry automation project is structured to avoid each one.

Key takeaways

• PMI's 2026 Pulse of the Profession found 31 percent of complex projects fail to achieve the full scope of their intended benefits, more than twice the rate for projects overall.
• CIO's 12 causes of IT project failure are about ownership, decisions, and people. None of them is a software problem.
• A steering committee with senior people from both the vendor and the customer answers three of the 12 causes in a single meeting cadence.
• A signed success criteria document, a first win on a minimum scope, and a ramp plan to full scope handle most of the rest.

You have probably lived through at least one of these: an ERP upgrade that ran two years late, a CRM rollout the sales team never logged into, or a "quick" integration that consumed a business analyst for six months and shipped with half the requirements.

So when someone proposes automating order entry, the skepticism is earned. The pitch sounds like every other pitch. The demo looks like every other demo. Then you are the one who has to explain to the CEO why the project that was supposed to free up the order desk instead created a new backlog.

The good news is that project failure is well studied. The causes repeat. That means a project can be designed against them before the kickoff meeting. This is how.

Why do IT projects still fail in 2026?

Because the causes are organizational, and organizations change slowly. CIO's feature quotes consultants from Kearney, West Monroe, PMI, and PMO Advisory, and their list has barely changed in a decade: no business owner, no clear success measure, no one empowered to decide, and change management treated as a communications plan. What has changed is the pace. AI now compresses the technical work, which exposes the organizational gaps faster.

Rick Catalano of AMIGO puts it this way in the CIO piece: "Too often there is no one empowered to make decisions, and too often project managers are left waiting for answers and then get asked why things are late." He calls it a cultural problem, not a project problem.

That framing matters for order automation. The technical piece, reading a purchase order and posting a sales order to the ERP, is now the fast part. The slow part is agreeing on which customers to automate first, who signs off on a business rule, and what "done" means. A project plan that only covers the technical piece is a plan for the easy half.

What are the 12 reasons IT projects fail?

Each of CIO's 12 culprits are paired with the mechanism in a well-run order automation project that addresses it. The rest of this post explains the mechanisms.

1. No trained project manager: the vendor runs the project with a named project lead. The customer does not have to lend a business analyst to learn project management on the job.
2. No alignment with business objectives: a discovery phase maps the order flow and states the business goal before any configuration starts.
3. Ambiguous measures of success: a success criteria document, signed by both companies within days of kickoff, defines Go-Live and Phase 1 Complete separately.
4. Not enough scrutiny of AI outputs: a human-in-the-loop review queue shows the team every extracted order before it posts, until the data earns trust.
5. Humans can't keep pace with AI: the workflow is designed around exceptions. People handle exceptions, not volume.
6. Resources mismatched to the plan: the customer's time commitment is named and scheduled, covering discovery interviews, rule reviews, weekly project meetings, and the steering committee.
7. Poor prioritization: go live on a minimum scope you know well. Complex order types are deliberately deferred to a later ramp or phase.
8. No business ownership: the customer's senior operations leader sits on the steering committee and signs Go-Live and Phase 1 Completion.
9. Sponsor not engaged: the steering committee meets on a fixed cadence, so sponsorship is a calendar commitment rather than a title.
10. Not all stakeholders involved: discovery covers everyone who touches an order, including customer service, pricing, account management, IT, and finance.
11. Slow or no decision-making: senior people from both companies are in the same room every two to three weeks with authority to decide.
12. Change management shortchanged: adoption is built into the milestones. The team sees real orders automated early and scope expands on a written ramp plan.

Who should own an order automation project?

The business should, and specifically the person accountable for the order desk's throughput and accuracy. Eric Stettler of Kearney says in the CIO piece that having the CIO drive process change instead of a business owner "would be a tail-wagging-the-dog scenario." IT can make sure the integration is sound. Only operations can decide to work differently.

This is why Y Meadows sets up a steering committee for every implementation. It includes senior management from Y Meadows and the customer's senior stakeholders, usually the operations leader who owns the order desk plus whoever owns the ERP relationship. It meets every two to three weeks, adjusted to how engaged the senior stakeholders are, and it reviews progress against the signed success criteria. Below it, the project teams from both companies meet weekly to do the work.

That single structure answers three of CIO's 12 causes at once. Business ownership (cause 8) is explicit because the customer's leader is in the room and signs the milestones. Sponsor engagement (cause 9) is a recurring meeting rather than a name on a charter. Additionally, decision-making (cause 11) happens at the table, because the people with authority on both sides are present. Lenka Pincot, chief of staff to the CEO at PMI, tells CIO that sponsors who only look at dashboards leave every decision to the project team, who may not have the information to make the right call. A steering committee exists to prevent that.

The second post in this series, on what a steering committee does on an order automation project, covers it meeting by meeting.

How do you define success for order entry automation?

In writing, before the first production order, with two separate finish lines. George Reed, CIO at auntEDNA.ai, frames it for CIO as a question: "If we were already done, what does winning look like?" Most order automation projects never answer it. They define scope (these customers, these order types) and assume success follows.

Y Meadows drafts a success criteria document at the kickoff workshop and both companies sign it within ten business days. It defines exactly which orders are in scope on five dimensions (channel, order type, customer, division, product), names every system the automation connects to, states how each common exception is handled, lists the business rules the system must enforce, and sets two finish lines. Go-Live means the system has proven it works on a minimum scope, validated through technical checks and user acceptance testing, and it starts a ten-business-day hyper-care period. Phase 1 Complete means the full agreed scope is live and performing in production over a rolling window of consecutive business days, and the customer has signed.

We’re splitting the two matters because the first is a technical milestone and the second is a business outcome. Conflating them is how projects get declared finished while the order desk is still doing the work by hand. The third post in this series, on how to define success criteria for order entry automation, goes through the document section by section.

Why does the first automated customer matter so much?

Because it is where the team decides whether to trust the system. The Y Meadows Success Roadmap starts with a discovery and assessment phase, then moves straight to a Quick Win: one regular customer with meaningful volume, deliberately not the most complex one. The team watches real orders from that customer get read, matched to their SKUs, validated against their rules, and presented for review.

This is prioritization (cause 7) done on purpose. Noah Fletcher of West Monroe tells CIO that most organizations are "not making hard choices on what are the really critical things to drive through," so too many people work on too many things. Picking a minimum scope and getting it to production before touching anything else is the hard choice, made early. The success criteria document then lays out a ramp plan from that minimum scope to the full Phase 1 scope, with a target date for each step, so expansion is a schedule rather than a hope.

It is also the first step of change management (cause 12). Nick Kramer of SSA & Co. tells CIO he has seen more projects fail from poor change management than from poor technology. The order desk does not adopt automation because a slide deck told them to. They adopt it because they watched it handle Tuesday's orders from a customer they know. The Success Roadmap describes this as learning to drive in an empty parking lot before merging onto the highway. Confidence first, then volume.

How do you keep AI outputs honest?

By showing every extracted order to a person until the data proves itself. Te Wu of PMO Advisory warns in the CIO piece that AI "can make stuff up," and that small errors riddled through a project add up and can sink it. He is talking about AI used to run projects, but the same discipline applies to AI that reads purchase orders.

Y Meadows Order Entry presents each order in a review queue: what was extracted, how customer part numbers were matched to your SKUs, which business rules were applied, and what was flagged. During the Quick Win the team reviews everything. As accuracy holds, the steering committee decides which order types graduate to zero-touch posting and which keep a review step. The scrutiny CIO calls for is built into the workflow rather than left to chance.

This also addresses cause 5, the mismatch between AI speed and human capacity. Wu's point is that AI moves faster than the people who have to act on its output, so work piles up unless the process is redesigned around exceptions. An order desk that reviews only exceptions can absorb far more volume than one that reviews every order. The success criteria document forces the design choice early: for each common exception (a customer that cannot be identified, an item code that does not match, a unit of measure that disagrees with the product master) the customer picks the handling in advance. That decision belongs to the order desk, not the software.

Who needs to be in the room during discovery?

Everyone who touches an order between the inbox and the shipping dock. Krista Phillips tells CIO about a multinational that rolled out a new technology and left an entire division out of the planning. The order desk equivalent is the pricing analyst who applies a contract discount from memory, the account manager who knows customer X always wants split shipments, and the IT administrator who owns the ERP integration user.

The discovery phase maps how orders flow today, where they get stuck, which customers cause the most rework, and which rules the team applies without writing them down. Those rules live in people's heads, and the only way to get them out is to interview the people. The success criteria document has a section for exactly this: the custom rules your team enforces that your accounting system does not. Skip someone and their rules do not make it onto that page, which surfaces later as an "AI error" that was a missing requirement all along.

Discovery is also where alignment with business objectives (cause 2) gets set. Shane McDaniel, CIO for the City of Seguin, Texas, tells CIO that misalignment "boils down to communication, awareness, being proactive, and holding people accountable." Writing down the business goal (fewer hours on data entry, faster order acknowledgment, capacity to grow without hiring) before configuring anything is the cheapest insurance a project can buy.

How much of the customer's time does an order automation project take?

Less than an ERP project, and it should be scheduled up front. Fletcher tells CIO that under-resourcing still plagues IT projects, and that AI makes it worse when executives assume the tool will do the work and staff the project thin. On an order automation project, the vendor does the configuration and integration. The customer's time goes to four things: discovery interviews, reviewing business rules and exception decisions, a weekly project meeting with the vendor's team, and the steering committee every two to three weeks.

Naming those commitments at kickoff, with hours and names, is how cause 6 gets handled. The order desk lead who will review the first hundred automated orders needs that time protected. The IT contact who will provide ERP credentials needs to know it is expected within days of kickoff, not whenever it fits. When the customer's contribution is specific, it gets staffed. When it is "we'll need some of your team's time," it gets squeezed.

This is also why the project manager question (cause 1) resolves differently here than in a typical internal IT project. Eric Bloom of the IT Management and Leadership Institute tells CIO that small and midsize projects get handed to a business analyst with no project training. An order automation project should come with its own named project lead from the vendor, so the customer's people can contribute their expertise about orders rather than learning to run a project.

What does this look like in practice?

A discovery phase that produces a written map of the order flow and a business goal. A success criteria document, signed by both companies within days of kickoff, that defines scope, integrations, exception handling, business rules, and two finish lines. A steering committee with senior people from both sides, meeting every two to three weeks against that document, with weekly project meetings underneath. A first win on a minimum scope, reviewed by the team, before anything expands. A ramp plan with dates to reach full scope. Exceptions routed to people and routine orders posted automatically, with the line between them decided in advance.

None of this is exotic project management. It is the ordinary discipline that CIO's experts say most projects skip. The difference on an order automation project is that the vendor can bring the discipline with them, so the customer does not have to build it from scratch.

If you have a project scar from the last rollout, bring it to the conversation. We will walk through how the Success Roadmap and steering committee would have handled it. Book a demo. Or start with the milestones themselves: download the Success Roadmap.

Sources

• Mary K. Pratt, "Why IT projects still fail," CIO, August 31, 2026. cio.com
• Project Management Institute, "Pulse of the Profession 2026: Driving Success in Complex Projects," May 2026. pmi.org
• Y Meadows, Success Roadmap (implementation guide). use.ymeadows.com/roadmap