The problems we are usually called about

How it presents

Marketing is spending, the form is being filled in, and the sales number is flat. The usual conclusion is that the leads are low quality.

What is usually true

Sometimes the leads genuinely are wrong, and the targeting needs work. More often the leads are fine and never got called — or got called two days later, by which point someone else had the job. Until response time is measured, the two causes are indistinguishable, and businesses reliably guess wrong because "bad leads" is the more comfortable explanation.

How we approach it

1. Measure before changing anythingInstrument capture and first contact so median speed-to-lead and contact rate become visible. This usually takes days, not weeks, and it settles the argument with data instead of opinion.
2. Close the response gapAutomatic assignment at capture, immediate acknowledgement to the enquirer, and a follow-up sequence that runs whether or not anyone remembers. No lead depends on a person having a good day.
3. Fix targeting only if the data says soWith contact rate healthy, lead quality can finally be judged honestly — and channel spend reallocated against qualified leads rather than raw volume.

How it presents

One or two people hold the process in their heads. Things work, but nothing can happen while they are away, and onboarding anyone new takes months.

What is usually true

This is rarely a documentation problem, which is why writing a manual never fixes it. The knowledge is procedural — dozens of small judgement calls about exceptions. It is load-bearing and invisible, and it becomes a hard ceiling on growth long before anyone names it as one.

How we approach it

1. Observe the real processWatch the work happen on live cases, including the awkward ones. The documented process is a summary; the exceptions are where the knowledge actually lives.
2. Encode the dominant pathAutomate the high-volume, low-judgement portion first, and route genuine exceptions to a person with full context attached. The aim is to stop spending attention where it was never needed.
3. Instrument the exception rateTrack how often the manual path fires. That number tells you where to extend coverage next, and whether the automation is quietly failing.

How it presents

What started as one shared sheet is now nine, with formulas nobody wants to touch, several conflicting versions of the truth, and a monthly reporting exercise that takes days.

What is usually true

Spreadsheets are excellent until concurrency and history matter. The failure is gradual: no single day is a crisis, but the cost of every decision rises because nobody trusts the numbers without checking them first. The genuine question is not whether to replace them, but which parts justify custom software and which are better solved by an off-the-shelf product.

How we approach it

1. Separate build from buyMost of what a spreadsheet does is generic and has a mature product behind it. We identify the genuinely differentiated part — usually one or two workflows — and scope custom build to that alone. We will say plainly when the answer is to buy.
2. Migrate with the data intactExisting records move across with history preserved and validated, so the new system starts trusted. A migration that loses history gets abandoned.
3. Ship narrow, then widenOne workflow in production and used daily beats a complete system in staging. Scope grows against real usage rather than a specification written before anyone touched it.

How it presents

A CRM was bought, configured, and is now largely ignored. Forecasts are assembled by asking people, and the pipeline reflects whoever remembered to log an update.

What is usually true

Adoption failures are almost never about training. A CRM gets ignored when using it costs the salesperson more than it gives back — duplicate entry, fields that serve reporting rather than selling, no automation of anything they actually find tedious. The fix is to make the system worth opening, not to mandate that it be opened.

How we approach it

1. Remove the duplicate entryConnect the sources leads already arrive through — website, phone, email, marketplaces — so records create themselves with campaign context attached.
2. Cut the fields nobody needsEvery required field is a tax on adoption. Keep what drives a decision or a workflow; delete the rest, including reports that were never read.
3. Make the pipeline joinable to revenueCarry first-touch attribution through to closed business, so the question "which channel produced revenue" has an answer that does not require a spreadsheet.