Call · 15 min
AI systemsMattia Esposito2 September 20267-minute read

Adaptive CRM. One place where the data is the true one.

The customer file on the office computer, the stock availability file in the warehouse, the contact list on the salesperson's phone. Three different truths about the same business, drifting a little further apart every week. This piece leaves only one, and keeps it up to date on its own.

In short

You write in one place only. Customers, requests, orders and availability sit in a single archive, and every screen reads from there. The second write disappears, and that is where divergence is born.

The fields follow your process. Statuses, steps and names are derived from how you work now, including those that exist only in your trade. That is why it is called adaptive.

The check happens when the data comes in. A code that doesn't exist or an impossible date are rejected immediately, instead of being found three weeks later by a customer.

This is the page for a single piece of the system. The other pieces, and the criterion for choosing which to start from, are on the services page.

What changes in practice

The simple question gets an answer in ten seconds. How much that customer bought in the last year, where that request stands, how many items there really are: today in many businesses it takes three open files and two people to interrupt, and the answer still comes back uncertain.

The second change is that nobody rewrites anything. The data goes in once, from the point where it originates, and from there everyone else sees it. When someone corrects it, who did it and when stays written down, so arguments about who was right end with a glance.

The problem with spreadsheets isn't that they are spreadsheets. It's that there are three of them, and nobody knows which of the three is up to date.

Why spreadsheets drift apart, and why nobody notices

In the spreadsheets businesses actually use, error is the rule, not the exception. Out of 85 operational spreadsheets combed through in six independent studies, 94% contained at least one error, with an error rate per cell between 1.2% and 2.5%.

The data is gathered by Raymond Panko of the University of Hawaii in What We Don’t Know About Spreadsheet Errors Today, table 2. His conclusion reads: «spreadsheet programs are not error-prone. People are error prone».

An error rate of 1% per cell seems small until you look at the size of real spreadsheets. In the same work, a census of two organisations finds 65,806 spreadsheets on internal servers, with an average of more than 4,000 formulas each. At numbers like these, the probability that the total at the bottom is wrong stops being a hypothesis.

Rereading doesn't close the gap. In the research on human error that Panko summarises, people find about 81% of simple errors and only 66% of complex ones, so a third of the difficult cases stay in even after a careful check.

Your process decides the fields, not the other way round

A catalogue product brings its own working model and asks the business to adapt: predefined fields, predefined statuses, predefined steps. It works when the business resembles the model, and in Italy it almost never does.

Here we start from the opposite. We look at how work is done today, write down the real statuses of a request, including those no product foresees, and the archive takes that shape. A producer who ships samples before the order has a status for samples, because in their trade that status exists.

The same goes for words. If you call something a pratica that elsewhere is called an opportunità, the archive writes pratica. A system that forces people to translate their own trade every time they write in it is abandoned within three months.

What the system does, step by step

Every piece of data comes in from a single point and every change leaves a log entry with author and time, so you can always trace back to how it was before.

StepWhat happensWhat you get
Collectionfrom today's spreadsheets

Existing files are imported with their history, duplicates included, and the duplicates are shown rather than merged at random.

You start from what you already have, without a week spent retyping master data.

Shapefields and statuses

The fields, statuses and rules are derived from your process during analysis, and can still be changed afterwards.

Those who work with it recognise their own words on day one, so they actually write in it.

Checkon the way in

Data is verified when it comes in: codes that must exist, possible dates, mandatory fields where needed.

Errors cost ten seconds now instead of a phone call to the customer three weeks from now.

Syncto your programs

Where management software can be accessed from outside the data flows on its own, where it can't the file to import is prepared.

Nobody has to change management software, and whoever uses the old program doesn't notice.

Historywho and when

Every change stays recorded with author and time, and the previous state can always be reread.

Arguments about who changed what last a glance instead of half a day.

The check at the moment of writing, which almost nobody builds

Almost all projects of this kind put the clean-up at the end: import everything, then spend a week fixing it. That is how the manual work you wanted to remove reappears under another name, and why the 94% measured by Panko concerns spreadsheets someone had already checked.

Here the check is at the entrance. An order without a price doesn't go in, a customer code that doesn't exist doesn't go in, a delivery date earlier than the order date doesn't go in. Whoever is writing finds out immediately, while they still have the document in front of them and remember what they were doing.

Duplicates are treated the same way. Two records that look like the same company aren't merged automatically: they are placed side by side with the differences highlighted, and a person decides. Merging the wrong two customers is damage you discover once the invoice has been issued.

This is also why the archive is the floor the other pieces stand on. Reminders, reactivations and follow-ups only work if someone knows, without doubt, who bought what and when.

Italian SMEs are on the other side of the gap

The advantage isn't theoretical, and it has been measured. In the 2025 European survey on the use of technology in enterprises, 65% of large enterprises use customer management software against 25% of small ones: forty points apart on the same tool.

The gap is even wider on the tools that read the data: 69% against 11% for business intelligence, according to Eurostat data published on 20 May 2026. Those whose data is in order know which customers deserve a phone call; those with three spreadsheets call in alphabetical order.

It should be said that the survey only counts enterprises with ten or more persons employed, so the smallest part of the Italian business fabric isn't even in the number. The full reasoning on the gap is on the page about our way of reading the sectors.

The same thing changes name with the trade

The archive is the same; the spreadsheet that replaces it today isn't. It is worth looking at your own case, because that is where you see what is being lost.

SectorThe spreadsheet that holds everything todayWhere you see it
Food and agricultureand export

The list of foreign distributors with the last order, the samples shipped and the agreed terms, updated by whoever remembers to do it.

The typical day of a small producer who exports

Hospitalityaccommodation and events

The calendar of requests with the dates on hold, the quotes sent and the deposits collected, scattered between a spreadsheet and a mailbox.

The pre-season of an accommodation business

Restaurantsand bars

The suppliers, the agreed prices and the regular customers of the big tables, which today live in the head of whoever has been on the floor longest.

The service of a dining room where the phone rings unanswered

What this piece doesn't do

It doesn't replace the management software and doesn't impose a new product on those in the business who already have their tools. It sits alongside, takes the data and gives it back, and where a program stays closed it stops one step earlier and delivers the file.

It doesn't decide for you who is a good customer. It keeps the data clean and shows it; qualification and reactivation are a different piece, handled by customer qualification and reactivation. The reasoning about the human constraint is on the page about the principles we build with.

It doesn't promise a return multiplier. Published estimates for customer management projects vary enormously depending on how much the system is actually used, and whoever quotes a single number is picking the end of the range that suits them. The number that counts is how much the second write costs you today, and it can be counted in a week.

Questions and answers

Do we have to throw away our Excel files?

No, and it isn't even worth trying on day one. Existing spreadsheets are imported with their history, and where someone has worked with them for years the sheet can remain as a read-only view that updates itself from the archive.

What disappears is writing in several places: you write in one place only, and read wherever you like.

What's the difference from a CRM bought on subscription?

A catalogue product brings its own working model and asks the business to adapt: fields, statuses and steps are those foreseen by whoever wrote it. Here the fields are derived from the process you already use, including the statuses that exist only in your trade.

It is also why we don't promise a return multiplier: published estimates for customer management projects vary enormously depending on how much the system is actually adopted.

Who guarantees the data inside is right?

The check happens when the data comes in, which is the only moment it is cheap. A customer code that doesn't exist, an impossible date or an order without a price are rejected immediately, instead of being discovered three weeks later.

A downstream reread isn't an alternative: in research on human error, people find about 81% of simple errors and 66% of complex ones, so some always stay in.

Do our management software and programs stay where they are?

Yes. The archive sits alongside what you have and doesn't replace it: where a program can be accessed from outside the data flows on its own, where it can't the system prepares the file in the layout that program imports.

Nobody has to change management software to make the rest work, and this constraint applies to every piece of the system.

How do you measure whether it's working?

With leads and reminders that are no longer lost, counted before and after over the same window. The second number is how many times the same data is written by hand in two different places, which at the start is counted by sample over a week.

The third is the time it takes to answer a simple question, such as how much that customer has bought in the last twelve months. Today in many businesses that answer requires opening three files and asking two people.

Notes on sources

  1. The 94% of operational spreadsheets with at least one error, the per-cell rates between 1.2% and 2.5%, the census of 65,806 spreadsheets and the detection rates of 81% and 66% are in Raymond R. Panko, What We Don’t Know About Spreadsheet Errors Today, 2016, table 2 and section 2. The table gathers 85 spreadsheets examined in six studies between 1995 and 2001, mostly financial models under audit: the sample is small and old, and we say so. The direction is confirmed by all the later studies cited in the same work.
  2. The 65% against 25% on the use of customer management software and the 69% against 11% on business intelligence are from Eurostat, survey on ICT usage in enterprises 2025, published on 20 May 2026. The survey covers European enterprises with ten or more persons employed, so it excludes micro-enterprises, and it compares large enterprises with small ones at Union level, not country by country.
  3. On the economic return we don't publish a multiplier. The most cited estimate on the subject, Nucleus Research's 8.71 dollars per dollar spent, comes from an analysis of selected cases, and later surveys by the same firm give much lower values. It is a range that depends on adoption, not a transferable promise.
  4. This page doesn't report results obtained for a client, because this piece hasn't yet been delivered to a client. The tests cited are functional checks carried out in testing.

The other pieces in this group

Requests and contacts lost between channels and languages

All the pieces, in the six groups

·The next step

Fifteen minutes, with your case in front of us.

How many different files have to be opened, today, to know how much a customer bought in the last year? If the answer is more than one, that is already the measure of the problem. In fifteen minutes on the phone we look at it together and tell you where it makes sense to start, even if we don't end up working together.

You get Mattia Esposito, who then builds the system: there's no salesperson in between. If you'd rather measure on your own before talking, the Diagnostico (in Italian) is twenty questions and five minutes.