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Data quality and reconciliation

Roll-ups that add up, exports that do not, and the checks that catch the difference.

Data quality and reconciliation

A CRM data quality scorecard: five fields, five checks, one number per rep

How to score CRM data quality from the export rather than from complaints: five fields that every coverage and pipeline measure depends on, owner, close date, stage, activity date and account identifier, the check for each, the completeness and validity rate per rep, why the score is reported beside the measures that depend on it, and the rule that a measure computed on data under a stated score is shown greyed.

16 Sept 20263 min read
Data quality and reconciliation

Account hierarchy: parents, subsidiaries and the level you actually sell to

How to build and use an account hierarchy for sales analytics: the levels that exist in most customers, group, legal entity, site, department, the one level where the buying decision is made and every measure is computed, the levels beneath kept as dimensions, the dated parent mapping that survives acquisitions, the identity that revenue sums identically at every level, and the two mistakes that produce forty customers where there is one and one where there are forty.

16 Sept 20263 min read
Data quality and reconciliation

B2B customer segmentation from the ledger, not from personas

How to segment a B2B customer base from data the company holds: the two or three fields that make a segment useful for norms, size, sector and channel, why behavioural fields like order frequency and product mix belong in the measures rather than the segment definition, the minimum segment size that makes a norm mean something, the test that a segmentation is good, and why personas do not survive contact with a ledger.

16 Sept 20263 min read
Data quality and reconciliation

Baseline and norm: what this account usually does, and what accounts like it do

The difference between a baseline, an account's own typical level from its own history, and a norm, what similar accounts do when the relationship is full, why the two answer different questions, has this account changed and how far is it from where it could be, which measures use which, surge and dormancy against baseline, gap and share against norm, the case where an account is at its baseline and far from the norm, and the rule that both are stated on the line that uses them.

16 Sept 20263 min read
Data quality and reconciliation

Control total and identity: the check against the world, and the check against itself

The difference between a control total, which tests an uploaded file against the figure the source system showed, and an identity, which tests the computed tables against each other, why both are needed and neither replaces the other, the failure each catches that the other cannot, a filtered export against a duplicated account, the order they run in, and what a report says when one of them is unavailable.

16 Sept 20262 min read
Data quality and reconciliation · Investment banking

Coverage officer transitions: handing over a client list without losing recency

How an investment bank's coverage group manages a banker's departure or move from the coverage file and the contact log: the clients whose last contact was with the departing banker, the days since any other banker touched them, the fee wallet at risk, the handover list ranked by it, and the ninety-day check that says which clients the new officer has actually met.

16 Sept 20262 min read
Data quality and reconciliation · Construction and building materials

Credit limit headroom: the accounts that stopped buying because they hit the limit

How a builders' merchant or trade supplier finds the accounts whose purchasing is constrained by their credit limit rather than by demand: headroom from the credit file and the ledger, orders held or refused for credit, the accounts at the limit whose purchase pattern flattened, and the two decisions that follow, a limit review for the good payers and a collections conversation for the rest.

16 Sept 20262 min read
Data quality and reconciliation

Credit notes and returns in revenue measures: net of what, and when

How credit notes, returns and rebates enter the revenue measures without breaking them: the rule that every measure is net of credits, the period a credit belongs to, the original invoice's or the credit's, the credit-to-original link that lets a return reduce the right customer, product and rep, uncoded credits as their own leak, and the identity that gross less credits equals the ledger's net figure on every roll-up.

16 Sept 20262 min read
Data quality and reconciliation

Currency and multi-entity roll-ups: one identity across several ledgers

How a company with several legal entities and currencies builds one commercial roll-up that still reconciles: the entity as a level above region, one reporting currency at stated rates per period, the rule that conversion happens once at the entity ledger and never in the report, constant-currency comparisons beside reported ones, intercompany revenue excluded by rule, and the identity that the sum of entities in reporting currency equals the consolidated figure.

16 Sept 20262 min read
Data quality and reconciliation · Industrial manufacturers

Direct and distributor channels without double counting: the manufacturer's reconciliation

How a manufacturer that sells direct and through distributors builds one roll-up where the same shipment is never counted twice: channel as a dimension, separate reconciliation per channel, point-of-sale data where it exists, and the assertion that channels sum to shipped revenue.

16 Sept 20263 min read
Data quality and reconciliation · Healthcare and med-tech

Facility identifiers: mapping ship-to locations to health systems for medical suppliers

How a medical device or supplies company rolls hundreds of ship-to addresses up to facilities and facilities up to health systems, the identifiers that make it repeatable, the assertion that catches a hospital under two systems, and why GPO compliance and product depth are wrong until this is done.

16 Sept 20263 min read
Data quality and reconciliation

Fiscal calendars and period cuts: why March is not always March

Why two reports for the same month disagree when one uses the calendar month and the other the fiscal period, the four period conventions that appear in a single company, calendar month, 4-4-5 fiscal periods, week-ending Sunday, and invoice-date versus ship-date, the rule that every export states its cut and every report inherits it, the identity that a year's periods sum to the year, and the trap of comparing this March to last March across a 53-week year.

16 Sept 20263 min read
Data quality and reconciliation · Pharma

Formulary status as a dimension: why call plans count the wrong accounts

How a pharmaceutical commercial team carries formulary and access status on every account so that reach, frequency and share are computed among the accounts where the product can actually be prescribed, the two lists that fall out, calls on blocked accounts and uncalled accounts with open access, and the dated status that makes a quarter's numbers comparable to the last.

16 Sept 20262 min read
Data quality and reconciliation

How to build a customer master from scratch: the fields that matter, and the ones that do not

A customer master is the file that says what each account is, and most companies have three that disagree. This guide sets out the eight fields a master needs for coverage and share-of-wallet analysis, identifier, parent, segment fields, size, owner, status and dates, where each comes from, the fields that seem useful and are not, the rule that one system is the source for each field, and the monthly check that keeps the master true.

16 Sept 20263 min read
Data quality and reconciliation

How to reconcile CRM to the ledger: the five mismatch types and what each means

A method for reconciling the CRM's account list and revenue to the finance ledger: the join on the account identifier, the five kinds of mismatch that come out, accounts in one and not the other, revenue with no owner, duplicates, timing, and identifier drift, what each one means, who fixes it, and the identity that says when the two systems agree.

16 Sept 20263 min read
Data quality and reconciliation

How to replace client names with IDs before uploading sales data

A practical method for pseudonymising a sales export before it leaves the firm: which columns identify a person or a client, how to build a stable ID mapping in a spreadsheet the firm keeps, what stays personal data under UK GDPR anyway, and how to check the file still reconciles afterwards.

16 Sept 20263 min read
Data quality and reconciliation

Identifier drift: when a system re-keys an account and the history breaks

What happens to every measure when a CRM migration, a merge or a re-numbering changes an account's identifier: the account appears new, its history appears lost, dormancy fires, concentration drops, and share of wallet resets. The dated identifier map that prevents it, the three ways drift is detected on upload, the rule that old identifiers are never reused, and the worked recovery after a migration that re-keyed a third of the base.

16 Sept 20263 min read
Data quality and reconciliation

Identity and reconciliation: the sum that must hold, and the work of making it hold

The difference between an identity, a sum that must be true by construction, region equals team equals person equals account equals the ledger, and a reconciliation, the work of finding why it is not and fixing the source, why the identity is checked on every upload and the reconciliation is done on the exceptions it lists, the three causes that account for most failures, and why a number is never adjusted to make an identity hold.

16 Sept 20262 min read
Data quality and reconciliation · Healthcare and med-tech

Invoiced price against contracted price per facility: the leak that looks like compliance

How a medical supplies company checks that what it invoiced each facility matches the price on the contract that facility is entitled to, from the invoice lines and the contract price files: overbilling that becomes a credit and a relationship problem, underbilling that is margin given away, the tier assignment errors that cause both, and the identity that ties the check to the ledger.

16 Sept 20263 min read
Data quality and reconciliation · Telecoms and connectivity

Maintaining the customer estate: the denominator in site penetration for B2B telecoms

Site penetration is only as good as the site count it divides by. This guide sets out where a business telecoms provider gets each customer's estate, how to date and source it, how to reconcile it to billing so closed sites do not linger, and the review cadence that keeps the number honest.

16 Sept 20262 min read
Data quality and reconciliation · Education

Multi-academy trusts and the contracting entity: getting the institution level right in education sales data

Why an education provider's coverage and renewal numbers depend on rolling schools, academies and legacy codes up to the entity that signs the contract, how to keep sites as a dimension underneath it, and the checks that catch a trust counted as ten small institutions.

16 Sept 20263 min read
Data quality and reconciliation · Pharma

Off-plan calls and plan versions: the two things that break pharma cycle reporting

Why reach and frequency numbers drift when the call plan changes mid-cycle or calls are logged against prescribers who are not on it, how to keep plan versions with dates so every call is measured against the plan in force, and how to report off-plan calls as their own line rather than losing them.

16 Sept 20263 min read
Data quality and reconciliation · Financial services

Opened and unused: the products customers hold and never use

How a financial services firm separates products held from products used, from the holdings file and the transaction ledger: accounts with no activity since opening, the share of a customer's products that are dormant, why a product count overstates the relationship, and the two lists that follow, activation for recent openings and attrition watch for products that went quiet.

16 Sept 20262 min read
Data quality and reconciliation · Oil and gas services

Operator name mapping: the unglamorous work behind basin coverage

Why an oilfield services company's coverage numbers depend on a mapping table from every operator name in every source to one identifier: subsidiaries, joint ventures and abbreviations, the unmapped-rig count that says how complete the table is, and how to maintain it as operators merge and rename.

16 Sept 20263 min read
Data quality and reconciliation · Foodservice distributors

Order guide compliance: what a kitchen was set up to buy against what it buys

How a foodservice distributor measures how closely each kitchen's orders follow the order guide it was set up with, from the order guide file and the delivery ledger: guide items ordered, guide items never ordered, off-guide items ordered instead, the substitution pairs that recur, the kitchens whose guide is stale, and why a low compliance figure is usually a guide problem before it is a customer problem.

16 Sept 20263 min read
Data quality and reconciliation · FMCG and CPG brands

Out-of-stock per store from sell-out gaps: the SKU that stopped selling on a Tuesday

How a CPG brand infers out-of-stocks per store per SKU from daily or weekly sell-out data without shelf audits: the SKU's own sales rate at the store, the gap that is too long to be chance, the lost sales valued at that rate, the stores and SKUs where gaps recur, and why the inferred figure is a list for the field team rather than a claim against the retailer.

16 Sept 20263 min read
Data quality and reconciliation

Outliers: the one-off order that breaks the norm, and what to do with it

How a single large order distorts every measure built on it, the norm it inflates, the run rate it doubles, the concentration it spikes, the share of wallet above 100 percent it produces, how outliers are detected from the account's own history and the segment's distribution, the rule that they are flagged and shown rather than removed, the medians that make norms robust to them, and the two kinds of outlier that are not errors at all.

16 Sept 20263 min read
Data quality and reconciliation

Pipeline hygiene: five checks to run on the CRM every week before the forecast call

Five checks on the open pipeline that take a minute from a weekly export and remove most of the argument from the forecast call: close dates in the past, deals without a next step or activity in a stated window, deals in the same stage past the team's own median stage duration, values unchanged since creation on late-stage deals, and duplicate opportunities on one account. Each with the count, the value affected and the rep.

16 Sept 20263 min read
Data quality and reconciliation

Product taxonomy for analytics: lines, families and SKUs, and which level each measure uses

Why a product list with four hundred SKUs produces whitespace everywhere and a concentration figure that means nothing, the three levels a product taxonomy needs, line, family and SKU, which measure is computed at which level, the rule that a SKU belongs to exactly one family and a family to exactly one line, the dated mapping that survives a range change, and the identity that revenue sums identically at every product level.

16 Sept 20263 min read
Data quality and reconciliation · Investment banking

Reconciling the desk to the benchmark submission: a quarterly checklist for institutional sales

A checklist for the quarter-end reconciliation between an investment bank's sales desk roll-up and the revenue it submits to its benchmark provider: product mapping, client mapping, period cut, joint coverage and the variance report that turns three weeks of email into one page.

16 Sept 20263 min read
Data quality and reconciliation · Financial services

Segment migration: when a customer moves band, the norm moves with them

How a financial services firm handles customers that cross a segment boundary during the year: what the norm was, what it becomes, why product fit and cross-sell measures jump at the boundary, and the reporting rule that shows the movement instead of hiding it as a gap that appeared from nowhere.

16 Sept 20263 min read
Data quality and reconciliation

Stated and estimated: the column that says how much a number is worth

Why every figure that depends on something the company does not hold, a customer's wallet, a project's value, a fee wallet, an estate, a held-away balance, carries a source column that says stated or estimated, the three grades of source, stated by the customer, norm from the company's own base, scaled from a public figure, what each grade lets a reader do, how a stated figure ages into an estimate, the rule that estimates never produce a claim, and how the source column changes the reading of a share, a gap and a list.

16 Sept 20263 min read
Data quality and reconciliation

Ten questions a head of sales operations asks, and the check that answers each

The ten questions a head of sales operations asks before anything is reported, does the CRM reconcile to the ledger, does every account have one owner, do the territories' quotas sum to the target, are the splits summing to one, is the pipeline clean, has any identifier drifted, which reps' data can be believed, did the definitions change, did the export match its control total, and what is on the exception list, each with the check that answers it, the identity behind it, and why sales operations owns the checks that everyone else's numbers rest on.

16 Sept 20263 min read
Data quality and reconciliation · Shipping and logistics

TEU and chargeable weight: keeping ocean and air apart in one roll-up

How a forwarder builds one customer view across ocean and air without ever adding a container to a kilogram: mode as a dimension, units per mode, reconciliation per mode to invoiced volume, revenue as the only figure that sums across modes, and the reporting mistakes that follow when the two are blended.

16 Sept 20262 min read
Data quality and reconciliation

The identity by industry: what has to sum to what on twelve desks

Every report on this site rests on an identity, a sum that must hold before any measure is read, and the sum is different on every desk: revenue to the ledger, TEU to booked TEU, seats to contracted seats, controls to the register, rental days to invoiced revenue. This hub gives, for twelve industries, the identity, the exports it joins, the failure it most often catches, and the guide where it is used.

16 Sept 20263 min read
Data quality and reconciliation

Why your territory totals don't match finance: the five reconciliation checks

The five checks that make a sales roll-up agree with the reported number: value is numeric, every level is filled, the hierarchy is a tree, no duplicates, and level totals equal the grand total. With the variance each one produces when it fails.

16 Sept 20264 min read
Data quality and reconciliation · Telecoms and connectivity

Estate currency on ten sites: the whole arithmetic on one page

The complete estate currency calculation on ten customer sites for one B2B telecoms account, small enough to check by hand: the services on the estate record, the services on the billing file, the join on the service reference, the orphan billed but not on the estate, the ghost on the estate but not billed, the site whose circuit was ceased and still on the record, the currency rate as services that agree over services on either file, the revenue on the orphans, and the assertion that estate services equal matched plus ghosts and billed services equal matched plus orphans, so a reader can reproduce every figure and then run it on their own estate and billing exports.

17 Sept 20264 min read
Data quality and reconciliation · FMCG and CPG brands

Inferring an out-of-stock at one store: the whole arithmetic on one page

The complete out-of-stock inference on one SKU at one store over thirty days, small enough to check by hand: the SKU's own daily sales rate excluding earlier inferred runs, the probability of a zero-sales run of each length at that rate, the confidence threshold, the run that crosses it and the run that does not, lost units at the rate and lost sales at retail, the missing-file day that is not a zero, and why the same run at a slow-selling SKU would not be inferred, so a reader can reproduce every figure and then run it on their own sell-out data.

17 Sept 20263 min read