From Chaos to Clarity: Common Mapping Mistakes Councils Can Fix Fast 

From Chaos to Clarity: Common Mapping Mistakes Councils Can Fix Fast 

From Chaos to Clarity: Common Mapping Mistakes Councils Can Fix Fast 

Process mapping is supposed to bring order to chaos. But in many councils, it ends up creating a different kind of mess – tangled diagrams, bloated documents, and confused staff asking, “Wait, where’s the actual process?” 

At Flowingly, we work with government teams across Australia and New Zealand who are tackling outdated systems, manual processes, and increasing compliance pressure. And more often than not, process mapping is where the trouble starts (and sometimes ends). 

Done well, process maps can transform how councils operate. Done poorly, they become yet another unused document sitting in SharePoint or locked in Promapp purgatory. 

So, what’s going wrong? 

Below, we unpack the most common mistakes councils make with process mapping – and how you can turn things around quickly. 

🧩 Mistake 1: Trying to Map Everything at Once 

Ambition is great. But trying to map your entire organisation in one go? That’s a one-way ticket to “overwhelmed and underdelivered.” 

It’s a mistake we see all the time. A new initiative kicks off. A process champion gets the go-ahead. Suddenly, there’s a spreadsheet with 87 processes to map “by end of quarter.” 

The result?

  • Teams are swamped. 
  • Maps end up half-done or overly generic. 
  • Nobody’s really sure what success looks like. 

The problem is this approach assumes all processes are equally valuable, equally broken, or equally known.
Spoiler: they’re not.
 

How to Fix it:

Start small and strategic. Focus on 1-3 processes that: 

  • Are high impact (touch lots of staff or citizens) 
  • Are manual and error-prone 
  • Are under pressure (e.g., LGOIMA, LIM, rates, dog reg) 

Map them properly. Validate them with the people doing the work. Then move to the next one. 

Ōtorohanga District Council didn’t start with every process. They started with one LGOIMA. That led to a 75% reduction in admin time. Wins like that build momentum. 

📚 Mistake 2: Using the Map as a Manual 

There’s a difference between a process map and an SOP. One shows the big picture. The other is the step-by-step. 

Too many councils try to cram every detail into the map: dropdown values, system screenshots, exact field names. The result? A visual nightmare. 

The result?

  • Maps become dense and unreadable. 
  • Staff get frustrated trying to follow them. 
  • Updating even one field becomes a chore. 

How to Fix it:

Use your map to show the flow: 

  • Who’s doing what 
  • In what order 
  • With what approvals 

Keep supporting material in separate SOPs or documents – and ideally, link them. (This is exactly what Flowingly’s upcoming SOP feature will enable: rich guidance embedded within the map, but not cluttering it.) 

By separating flow from instruction, you make both easier to use – and way easier to update. 

🧠 Mistake 3: Leaving Out the People 

Process mapping isn’t just a technical task – it’s a people one. Yet, in many councils, maps are created in a vacuum. 

A BA interviews a manager, drafts the map in isolation, and sends it out for “approval.” Meanwhile, the people actually running the process haven’t been consulted at all. 

The result?

  • The map doesn’t reflect reality. 
  • Staff don’t trust or use it. 
  • It’s outdated before it’s even published. 

How to Fix it:

Involve the people who live and breathe the process. Let them contribute and challenge assumptions. It can be as simple as: 

  • Asking frontline staff to walk you through a typical day 
  • Capturing exceptions they handle (but no one documents) 
  • Sharing a draft map and inviting feedback in plain language 

Collaboration is easier when your mapping tool is simple and accessible. That’s why Flowingly’s draganddrop builder is designed for everyone not just process pros. 

🔄 Bonus Mistake: Confusing Mapping with Automation 

It’s easy to conflate mapping and automation. After all, both aim to improve processes. But jumping into automation without a clear, accurate map is like building a house without a blueprint. 

The result?

  • Automated processes replicate existing inefficiencies 
  • Compliance gaps get missed 
  • Exceptions bring everything to a halt 

How to Fix it:

Map first. Then automate. Use the map to identify: 

  • Bottlenecks 
  • Manual handoffs 
  • Compliance risks 
  • Data collection points 

Only then should you start designing automation workflows with a clear understanding of the real process, not a guess. 

At Tauranga City Council, clear process maps made it easier to identify what not to automate, saving their team time and headaches. 

📋 What Good Looks Like 

Let’s talk about what mapping success looks like in the real world. 

Ōtorohanga District Council

  • Before: Ad hoc email handling of LGOIMA requests, no central view, high admin burden.
  • After: Standardised process map with clear roles, deadlines, and automated tracking.
  • Result: 75% reduction in admin time. Faster responses. Less stress at audit time.

Tauranga City Council

  • Before: Multiple tools, no clear process ownership, staff reluctant to engage.
  • After: Easy-to-follow Flowingly maps built collaboratively with business teams.
  • Result: Full council adoption in 4 weeks. Better visibility, better outcomes.

Waitomo District Council

  • Before: High staff turnover made onboarding tough. No consistent process documentation. 
  • After: Simple, visual process maps captured team knowledge. 
  • Result: Onboarding became faster and smoother – and knowledge stuck around. 

These councils didn’t get everything perfect from day one. But they took the right first steps: mapping what matters, mapping it well, and mapping with people. 

Final Thoughts 

Mapping doesn’t need to be a 6-month project. It doesn’t need consultants. And it definitely shouldn’t be a once-and-done exercise. 

The best councils treat process mapping as a muscle – not a milestone. They map collaboratively. They map clearly. And they use those maps to drive real improvement. 

With Flowingly, you can go from mapping chaos to clarity in weeks – not months. And if you’re ready to unlock the full value of your processes, we’re here to help. 

Let’s make process improvement a team sport (and finally retire that old flowchart in the shared drive). 

Want to see what smart mapping looks like in action? 
Book a demo and we’ll show you how real councils are actually getting it done. 

“Did You Get My Email?” – The Most Dangerous Words in Local Government

“Did You Get My Email?” – The Most Dangerous Words in Local Government

“Did You Get My Email?” – The Most Dangerous Words in Local Government

Every council has that moment. 

A compliance deadline is looming. A high-risk request is floating somewhere in the ether. And someone, somewhere, is muttering the phrase that sends a chill down every governance officer’s spine: 

“Did you get my email?” 

Those six words might seem harmless. But in the world of LGOIMA, OIA, audits, and compliance requests, they can signal the beginning of a costly paper trail… or a PR nightmare. 

The HighStakes World of Public Sector Compliance 

Local governments across New Zealand and Australia are facing a tidal wave of information requests – with LGOIMA volumes up 200%, election-season scrutiny, and ratepayer questions sharper than ever. 

The kicker? These requests often land on a single person’s desk, supported by a spreadsheet, a shared drive, and blind hope that nobody misses the deadline. 

Every missed reply, every buried document, and every misinterpreted risk level can turn into a headline. 

In short: your inbox is now a reputational risk. 
 

What’s Really Behind “Did You Get My Email?” 

That question is a symptom, not the cause. Here’s what it actually reveals: 

Lack of visibility

No one knows where a request is in the process or who owns it. 

Scattered communication

Juggling hallway conversations and email threads, while trying to keep track of where requests are at. 

No risk triage

Executive teams and legal aren’t looped in until it’s too late. 

From Inbox to Impact: How Councils Are Changing the Game 

Councils like Ōtorohanga District have shown that the right process can turn a compliance nightmare into a well-oiled machine. What used to be a frantic juggle of emails, spreadsheets, and office walkarounds can be turned into a clearly defined, automated workflow. 

Now, when a request comes in, it’s logged, triaged, and tracked in real time. The system assigns the right people, sets clear deadlines, and even sends reminders before anything slips through the cracks.  
 
No more guesswork. No more calendar counting to hit the 20-day mark. 

Risk management? That’s built in. High-risk or media-sensitive requests are automatically flagged and escalated. And with a complete audit trail, every comment, decision, and document is captured-ready to defend if scrutiny arises. 

The best part? Teams no longer feel overwhelmed. The average turnaround time dropped to five days. Staff aren’t hiding from LGOIMAs in the corridor. And for the first time, leadership has full visibility into what’s being handled, by whom, and when. 

In short, councils are no longer just reacting. They’re in control. 

Why This Matters Now

With regulatory complexity on the rise, skill shortages across the sector, and headlines just one mistake away, local government can’t afford to run high-risk processes on low-resilience systems. 

If your compliance processes rely on memory, spreadsheets, or that one person who “knows how it works,” you’re not just at risk – you’re already behind.

So, What’s the Fix? 

It starts with recognising that inboxes aren’t workflows. That process knowledge shouldn’t walk out the door with retiring staff. And that “Did you get my email?” should never be the first sign something’s gone wrong. 

Instead, councils are turning to no-code automation platforms like Flowingly to: 

  • Build transparent, step-by-step workflows in hours (not months)
  • Empower frontline staff to contribute without relying solely on IT 
  • Create audit-ready records – without the scramble 
  • Reduce stress, risk, and operational bottlenecks 

Did Somebody Say AI? 

Councils like Ōtorohanga are already ahead of the curve with streamlined, automated LGOIMA workflows. But with AI-powered workflows in Flowingly, teams can unlock even more value – without needing to expand headcount.

1. AI-Driven Email Triage 

Instead of relying on one person to manually read and route incoming LGOIMA requests, AI can help: 

  • Automatically categorise emails and route them to the right team (even when subject lines are misleading) 
  • Extract key request details from the body of the email
  • Flag priority or sensitive items for escalation (e.g. media-related or privacy-heavy requests).

This means governance teams can respond faster, with less manual sifting, and no risk of emails falling into inbox black holes. 


2. Sentiment & Risk Analysis at Intake

When a request is submitted through a public form or email, AI can assess: 

  • The tone and sentiment of the request – helping pre-empt public relations risk
  • The topics and entities mentioned (e.g. land use, budget cuts, climate resilience), tagging high-risk subjects for senior review.

For example, a request that uses neutral language but references “ratepayer privacy” or “fraud investigation” could be automatically escalated, ensuring your CE and legal team aren’t blindsided at day 19. 


3. Public Feedback & Submission Summaries

For high-profile or consultation-related requests, councils can use AI for real-time sentiment analysis to: 

  • Understand public themes and opinions across similar requests, 
  • Generate summary reports from free-text submissions – helping you respond faster with tailored messaging or proactive FAQs.

This isn’t theoretical. Teams are already using AI in Flowingly to enhance their processes today.


💡 Want to see these use cases in action?
Check out our webinar with Incendo – How Teams Can Transform Customer Experience Using AI. You’ll see how councils are combining Flowingly + AI to supercharge service delivery. 

Ready to Replace Chaos with Confidence? 

Whether it’s LGOIMA, internal audits, privacy requests or contractor approvals-Flowingly helps councils map, manage and automate processes that matter. 

👀 Want to see what that looks like? Check out how Flowingly can help government teams or get in touch with our team for a walkthrough. 

Because when your LGOIMA process is mapped, automated and AI-enhanced… “Did you get my email?” is no longer the most dangerous phrase in local government. 

It’s been replaced by something far worse: 
“We’re out of coffee.” 

4 Ways Teams Are Using Flowingly & AI Right Now

4 Ways Teams Are Using Flowingly & AI Right Now

4 Ways Teams Are Using Flowingly & AI Right Now

Let’s be honest—everyone’s banging on about AI, but how many organisations are actually using it to solve real problems? 

The gap between AI hype and practical implementation is wider than most vendors want to admit. That’s why we’re cutting through the noise to share how teams are combining Flowingly with AI to create genuine improvements in both customer and employee experiences. 

In our recent webinar with Liam from Incendo, we explored use cases that aren’t theoretical “someday” implementations—they’re happening right now, delivering real value. No fancy computer science degree required. 

1. Submitting Paper Forms into Flowingly

Ever tried to convince people to stop using paper forms? It’s about as easy as getting your nan to understand Instagram Stories. 

The reality is stark: organisations spend months (sometimes years) trying to wean staff off paper, burning through budget and patience. Projects close, benefits aren’t realised, and you’re back to square one—with a stack of paper forms still sitting on the counter. 

Here’s an approach that’s actually working: 

Stop fighting the paper battle

Let people use the formats they’re comfortable with

Use AI to do the heavy lifting

Document processing models extract information automatically and accurately

Allow multiple entry points, one workflow

Whether it’s email attachments, front desk submissions, or website forms 

What’s really happening behind the curtain: This AI use case works by mapping out where fields like “name,” “address,” and “phone number” typically appear on your standard forms. Unlike generic text recognition tools that can get confused by different layouts, this approach knows precisely where to look for each piece of information on your specific forms. 

The mind-blowing part? You only need to show the AI model about five examples of completed forms—some neat, some messy, some typed, some handwritten—and suddenly they’re capturing information with 98% accuracy. That means your team can stop manually entering data and start handling the parts of their job that actually require human judgment. 

The system is smart enough to know that scribble in the name field is still a name, even when someone’s messy ‘z’ looks suspiciously like a ‘2’. It pulls all this information straight into your workflow without anyone having to squint at bad handwriting or manually type things into multiple systems. 

The key insight? Change management doesn’t have to mean forcing people to abandon familiar processes—it can mean making those processes work better behind the scenes. 

2. Smart Email Triage & Responses

Many organisations face a perfect storm: improve customer experience while cutting budgets. All the while customer queries are becoming more complex, volumes have increased, and customer expectations keep getting higher and higher.

Meanwhile, teams are stretched thin, with less time to carefully consider each message. The inevitable result? Rushed, generic responses that leave customers feeling like an afterthought. Staff end up spending precious mental energy just deciding where to route messages, leaving little bandwidth for crafting thoughtful, personalised replies.

Here’s an approach that’s actually working: 

Auto categorisation

AI reads incoming emails and identifies the appropriate department 

Content summarisation

Key points are extracted, ensuring nothing gets missed 

Response recommendations

Suggested replies maintain consistent service quality 

What’s really happening behind the curtain: This isn’t just glorified keyword searching that sees “dog” in a subject line and mindlessly routes it to animal control. We’ve all experienced that kind of “smart” system, and it’s about as smart as a goldfish with amnesia.

Instead, it’s using natural language processing to actually understand the content and intent of messages. In the demo, someone deliberately tried to trick the system with a misleading subject line about dogs, but the content was clearly about litter in parks. The system analysed the full message context, ignored the red herring in the subject line, and correctly routed it to the parks team.

The AI reads through the entire message, identifies the main topics being discussed, and makes intelligent decisions about categorisation. It also extracts the key points that need addressing, ensuring nothing gets missed in lengthy emails.

The game-changer? Everyone from the brand-new temp to your most experienced staff can now focus on giving great answers instead of playing email detective. The system suggests where messages should go and offers response ideas, but humans still bring the judgment, empathy, and decision-making that no AI can match.

It’s not just pulling canned responses either. The system actually crafts suggestions based on what the person is specifically asking about—capturing your organisation’s voice while addressing the particular points raised. No more copy-pasting the same generic template and hoping it sort of fits.

This approach means consistent customer service without the staffing overheads—and without the risk of points being missed in busy inboxes.

The key insight? You don’t need to hire more people to improve service quality—you need to give your existing team tools that eliminate the low-value work so they can focus on what matters: the human connection.

3. ID Document Processing

Let’s face it—manually checking IDs and inputting data is about as exciting as watching paint dry. It’s also a breeding ground for errors that can have serious consequences.

Think about how many places you handle identification documents: new employee onboarding, customer verification, contractor certifications. When humans manually process these, mistakes happen—dates get mistyped, documents get misfiled, and suddenly someone’s been driving company vehicles with an expired licence for two years.

Here’s an approach that’s actually working: 

Leverage pre-built AI models

No need to train systems on every possible ID type

Handles imperfect inputs

Process photos with glare, odd angles, and poor resolution

Automate document management

Save to SharePoint with consistent naming conventions

What’s really happening behind the curtain: Unlike the paper form solution that needs training on your specific documents, this implementation leverages pre-built AI models that already understand identification documents from around the world. 

The system uses computer vision technology that’s been trained on thousands of different ID types—passports, driver’s licenses, national ID cards—from dozens of countries. It knows where to find key information on each document type, regardless of the format. 

What makes this particularly clever is that it doesn’t just capture text—it understands document structure. It knows the difference between an issue date and expiry date. It recognises when a string of characters is a license number versus an address. And it does this even with imperfect images that have glare, weird angles, or poor lighting. 

When verification from third parties (like police) is needed, Flowingly’s external actor feature can give those outside your organisation a secure way to contribute to the workflow without the usual email ping-pong. 

Instead of monitoring mailboxes and manually attaching returned documents, external parties simply click a link that pulls them directly into the workflow, where they can submit their verification. The workflow continues automatically once they’ve contributed. 

The result? A process that’s faster, more accurate, and creates a proper audit trail without anyone having to manually save documents or remember naming conventions. 

The key insight? The most expensive mistakes are often the most mundane ones—a mistyped date, a misfiled document, a missed verification. Letting AI handle these details isn’t just about efficiency; it’s about reducing significant organisational risk.

4. Sentiment Analysis That Actually Tells You Something Useful

We’ve all been there—staring at pages of survey responses or feedback submissions trying to make sense of what people are actually saying. By the time you’ve made sense of it all, it’s usually too late to do anything meaningful with the insights.

That’s where the fourth use case comes in: real-time sentiment analysis and theme extraction from public submissions, surveys, or feedback.

Every organisation has talented people stuck wading through mountains of feedback—whether it’s council submissions, customer surveys, or internal staff sentiment. These folks could be identifying critical insights and taking action, but instead they’re drowning in a process that’s typically slow, subjective, and backward-looking.

Here’s an approach that’s actually working: 

Automated sentiment detection

Understand emotional tone beyond simple positive/negative

Geographic sentiment mapping

Visualise patterns by location to spot regional concerns

Real-time dashboards

See results as they come in, not weeks after collection ends

What’s really happening behind the curtain:

This implementation uses multiple AI technologies working together to make sense of qualitative feedback—the kind of free-text responses that traditionally require hours of human analysis.

The system uses sentiment analysis algorithms to determine the emotional tone behind submissions. But it goes beyond simple positive/negative classification—it can detect nuances like “concerned but supportive” or “strongly opposed on specific grounds,” giving you a much more nuanced understanding of public opinion.

The AI doesn’t just look at individual submissions in isolation. It analyses patterns across all responses, using natural language processing to identify recurring themes and topics. This is not simple keyword counting—it’s understanding concepts even when people express similar concerns using completely different words.

What’s particularly clever is how it condenses complex feedback into actionable insights. The system automatically generates thematic summaries—short phrases that capture the essence of what people are saying about specific aspects of your proposal. This transforms pages of feedback into digestible insights that decision-makers can actually use.

The kicker? This happens in real-time, not weeks after your consultation period ends. Most survey results or submission analyses are produced after everything’s finished—when it’s too late to adjust your approach or messaging. With live insights, you can course-correct while your consultation is still active, ensuring you get more representative feedback.

The key insight? The true value of feedback isn’t in collecting it—it’s in how quickly you can understand and act on it. Real-time analysis transforms feedback from a retrospective exercise into an active guidance system for decision-making.

These four examples show how organizations are using AI today – not in some distant future. The key is using AI to handle repetitive tasks while keeping humans in control of decisions and customer relationships.

The most successful implementations:

  • Free people from data entry to focus on customer service
  • Improve consistency while preserving human judgment
  • Automate document handling to reduce costly mistakes
  • Turn feedback into actionable insights in real-time

Want to see these solutions in action? Watch our webinar with Incendo where we demonstrate exactly how these use cases work and how they’re built. Or get in touch for a demonstration of how Flowingly and AI can transform your processes without the usual implementation headaches.