Handbook

Part II · Understanding the problem · Chapter 4

Reframing the ask

The technology a customer asks for is a clue, not a diagnosis. How to find the problem underneath, and say so.

12 min read

Most customers arrive with a solution already chosen. Sometimes it is exactly right. Often it is a sensible guess made by someone a long way from the work. Your job is to take the request seriously enough to check it.

What you'll take away

  1. 01Why a requested solution is the customer's best guess, and what it tells you.
  2. 02Six common requests and the problems that often sit underneath them.
  3. 03How to test a diagnosis before you stake the project on it.
  4. 04Four replies to any request, and how to give the awkward ones.
  5. 05How to change a sponsor's mind with a test rather than an argument.

The request is a best guess

When a sponsor asks for "an agent" or "a chatbot", they are telling you three useful things: something hurts, they believe technology can help, and they have probably promised someone a result. They are not telling you what the problem is. That is your job to find out.

What they ask for"An AI chatbot for our website"What they feelToo many contacts, staff stretched, slow repliesWhat is happeningMost contacts ask where an order is; the status lives in a courier systemWhat would fix itSend status proactively; a narrow assistant for what's left
Fig 1. Each layer down is closer to something you can fix. Discovery is the work of getting from the top row to the bottom one.

Building the literal request is rarely neutral. If the real cause is somewhere else, you have spent the budget, the sponsor still has the problem, and now they also have a tool that does not work. Reframing is not arrogance. It is the most useful thing an outsider can do.

Six requests and what is often underneath

These patterns recur often enough to be worth knowing by heart. They are not rules. Each is a hypothesis to test.

The requestWhat is often underneathA better first move
"A chatbot for our website"One question type, usually status, makes up most of the volume, and the answer already exists in a systemSend that status proactively; scope an assistant for the remainder
"AI to write our proposals"Drafting takes a day; waiting for pricing and legal sign-off takes two weeksFix the approval route first; then templates and drafting help
"A voice bot for our phone line"Most calls come from one broken step on the website, such as a password resetFix that step and watch call volume before scoping a bot
"Predict which customers will leave"Nobody has time to act on a list; the score lives outside the daily toolA short ranked queue with reasons, inside the tool people already use
"Summarise all our meetings"The pain is lost follow-ups, not long meetingsExtract decisions and owners into the tracker the team already uses
"AI to check every supplier invoice"Nine in ten mismatches come from two suppliers who use their own formatsAgree a format with those two; automate checks on the rest

Testing a diagnosis

A reframe is a claim, and claims need evidence. Before you take one to a sponsor, try to prove yourself wrong.

  1. 1

    Sample real cases

    Pull the last 50 or 100 items of work: tickets, claims, documents. Categorise them by hand. Twenty minutes with a spreadsheet beats a week of opinions.
  2. 2

    Find the dominant failure

    Usually one or two categories account for most of the pain. Name them, with counts.
  3. 3

    Ask what would falsify your story

    If you believe misrouting causes the delay, check whether correctly routed cases are actually fast. If they aren't, your story is wrong.
  4. 4

    Price the alternatives

    Fixing the data, changing the process, a rule, a small model, a large model. Put a rough cost and timeline next to each.
  5. 5

    Find the smallest test

    What could you change in a week that would show whether the diagnosis is right? Run that before proposing anything big.

The cheapest experiment that could prove you wrong is the most valuable thing you can propose.

Four replies

Once you have looked at real cases, every request gets one of four replies. Say which one out loud. The costly outcome is not disagreement; it is a quiet yes from someone who doesn't believe in what they are building.

What the cases showedYesthe evidence backsthe request as askedYes, smallerright idea, start withone slice of itSomething else firstfix the cause, or amissing owner or ruleNonot worth it,or not safe
Fig 2. Pick the reply the cases support, say it plainly, and say what evidence would change it.
  • Yes. The request holds up. Build it, and enjoy the rare simple engagement.
  • Yes, smaller. Right idea, too much at once. Start with one team, one document type or one region, and earn the rest.
  • Something else first. The real cause sits elsewhere, or a prerequisite is missing: nobody owns the data, the rule isn't written down, access hasn't been granted. Fix that, then revisit the request.
  • No. It won't pay off, or can't be done safely. Uncommon, and worth a great deal to a customer when said early.

Saying it without making anyone wrong

The sponsor made a reasonable call from where they sit. Frame what you found as the project already succeeding: their initiative uncovered the real problem, faster and cheaper than building the wrong thing would have. Lead with the cases, not your opinion. Twenty real examples sorted on a slide persuade more than any argument, because the sponsor reaches the conclusion themselves.

Change minds with a test, not a debate

Sometimes the sponsor still prefers their original idea. Don't try to win the argument. Propose the smallest test that would settle it, and agree up front what result would change whose mind.

  1. 1

    State both views as predictions

    "If you're right, a chatbot will resolve most contacts. If I'm right, a status text will remove half of them by itself."
  2. 2

    Pick a test that takes days, not months

    Send status texts in one region for two weeks; compare contact volume with a similar region that didn't get them.
  3. 3

    Agree the decision in advance

    "If volume drops by a third or more, we do the texts everywhere and scope a smaller assistant. If not, we build the chatbot."
  4. 4

    Report it straight

    Whatever happens. Being proved wrong on a cheap test costs you nothing and earns a great deal of trust.

Try it

Reframe a request

A hotel group's revenue director asks for "an AI that sets room prices automatically". In two days of discovery you learn: revenue managers already use a pricing tool, but override it on about 40% of nights; overrides are usually for local events the tool does not know about; one hotel has no revenue manager and never overrides; and the director's bonus depends on revenue per available room.

Write a diagnosis, pick one of the four replies, and draft the sentence you would open with when you present it.

Write your answer down first, then reveal the worked answer

Diagnosis. Pricing is already automated. The gap is that the tool lacks local-event information, so people override it, and the one hotel without a manager can't correct it at all. A new pricing model trained on the same inputs would hit the same blind spot.

Reply: something else first. Feed local events into the existing tool, or give managers a quick way to record events that the tool learns from. Measure override rates and revenue per available room before and after, starting with the unmanaged hotel and one managed hotel.

Opening sentence. "You want higher revenue per room, and I think we can get it faster than by replacing the pricing tool. Your managers already correct it on four nights in ten, almost always for local events it can't see." A strong answer uses the override data as evidence and ties the proposal to the director's own metric.

Practise the skills