70% of technology projects fail because of people, not the technology. That number hasn't moved in 20 years. Senior change management, embedded in your project, fixes that.
Three services, built for three different moments in a project. Find yours below.
"We're six weeks from go-live. The tech is ready. But the team isn't. And I don't know how to fix it."
Senior change expertise embedded in your project on a flexible, part-time basis. AI-enhanced for faster insights. You get Sheena inside your project — independent from your tech provider, trusted by your exec team, and focused on the one thing that determines whether your rollout lands: your people.
Since December 2025, Australian employers must manage psychosocial hazards — including poor change management — with the same rigour as physical risks under WHS law. Poor change management is now a named legal liability. Independent change support creates a clear paper trail of due diligence.
"We implemented the system. Six months later, nobody's using it the way we intended."
The gap between go-live and genuine adoption is where most technology investments are lost. People use workarounds. Leaders don't model the change. Nobody wants to say they don't understand it. This is fixable — but not with another round of system training. It takes human-centred capability building.
3,000+ people trained across SAP, Salesforce, Oracle, and more. Delivered in banking, government, FMCG, education, and not-for-profit.
"We're rolling out AI tools. The technology is fine. Our people are the problem."
AI triggers a different kind of resistance. It's not just about learning a new system — it touches job security, identity, and trust in a way that standard technology rollouts don't. The messaging that works for a Salesforce implementation will not work here.
From AI readiness to full adoption — the people side of artificial intelligence, properly managed. Start free with the Risks and Actions Report and escalate to full support as you need it.
95% of AI pilots are failing — not because the technology doesn't work, but because the people side wasn't managed. AI super-users save 9 hours a week. Laggards save 2. The gap is a people problem, not a product problem.
Read: 95% of AI pilots are failing →After 20 years and 50+ projects, the pattern is clear: change fails when the system gets more attention than the people. Every engagement follows the same four-stage framework.
Understand the real risk profile. Who's resistant, who's fragile, who's being managed poorly. What the SCARF triggers are — status, certainty, autonomy, relatedness, fairness — and where they're firing.
A change strategy built around the employee experience — not the system. Communication sequencing, stakeholder priorities, and engagement approaches that match the actual people, not the org chart.
Embedded work — workshops, advisory, communications, interventions. Responding to what's actually happening on the ground, not what the project plan assumed would happen.
Adoption doesn't end at go-live. Embedding new ways of working, tracking genuine adoption (not just logins), and responding to the long tail of resistance that shows up after the project closes.
Senior change specialist across banking, government, FMCG, education, and not-for-profit. From Salesforce to SAP to Oracle — Sheena has led the people side of major system implementations, and now builds the AI tools that make change management smarter.
BSc Management Sciences · Grad Cert Change Management · Masters Business Leadership & Coaching
Yes. A project manager manages scope, budget, and timeline. A change manager manages people's readiness to adopt what the project delivers. Both are needed — but they're solving different problems. A project that's on time and on budget still fails if people don't use the system.
The failure rate for technology projects hasn't moved in 20 years (still around 70%) because organisations keep investing in better project management without investing in the people side. Those are separate disciplines.
Cost scales with project complexity, team size, and rollout stage. Fractional engagements are typically scoped per project — most run 3–9 months at 1–2 days per week. For organisations under 12 months from go-live, fractional support is almost always more cost-effective than a full-time hire.
Workshops and training programmes are quoted on scope — half-day workshops start from $3,500. The Risks and Actions Report is free with no sign-up required.
The best starting point is a call. Scope and budget usually become clear quickly.
Yes — and this is often the most effective model. Tech providers handle the system configuration, integration, and technical training. Sheena handles the people side: resistance, readiness, communications, and adoption. The two roles are complementary, not overlapping.
Many technology providers bring Sheena in specifically because their clients need human-side support that goes beyond what the provider is scoped to deliver. If you're a tech provider whose clients are struggling with adoption, get in touch.
No. Post go-live resistance and low adoption are common — and fixable. The Training and Workshops service is designed specifically for this moment. The key is understanding what's actually blocking adoption (it's usually not what people say it is) and then addressing it with the right intervention.
The earlier you act the better, but "too late" would mean the organisation has already written off the investment. Most haven't.
That's often the best time to bring in independent change support. Resistance always has a root cause — and it's usually fixable once you name it directly. The most common causes are: insufficient certainty about what's changing, no perceived voice in the process, and fear about job impact that nobody's addressed head-on.
An independent change manager can say things that project sponsors and line managers can't — because they're not inside the power dynamic. That independence is often what breaks a logjam.
The psychology is the same. What's different is the specific resistance patterns that AI triggers — particularly around job security, identity, and trust in the technology. People aren't just learning a new system. They're wondering whether the technology is going to replace them, and nobody is addressing that directly.
The messaging that works for a Salesforce rollout will not work for an AI rollout. AI literacy workshops need to be human-centred, not technical. The change strategy needs to actively address the job security signal before it metastasises into blanket resistance.
Try the free Risks and Actions Report and get your risk level plus a team-by-team action plan in minutes. Or book a call to talk through your project directly.