Data Organisation
RemedialHourlyFor Claims Consultants & Consultancies
I take the raw cost records behind your claim and structure them into one claim-ready dataset: every line dated, sourced and allocated to its head. The measuring cannot start until someone has done it, and it should not be your senior people.
The problem
Every quantum build starts with the same problem: the cost data arrives as chaos, with invoices in one folder, timesheets in another, three generations of the account spreadsheet holding three rival totals, and a ledger export that reconciles to none of them. None of it is usable until someone has read it, dated it, matched it and decided which version is true. So the practice's most expensive people spend their first week sorting paper, or the sorting gets skipped and heads get priced from whichever spreadsheet was open, and the claim ends up with figures its own records contradict.
The solution
You send the records as they come, straight off the job. I reconcile the sources against each other, strip the duplicates, resolve the rival versions with the survivor stated, and build the lot into one dataset in native Excel: every cost line dated, allocated to its head of claim and traced to its document. With it comes the method note and validation log: every source and period graded complete, partial or unreliable, every interpretation rule recorded, and the records that would close the gaps named. Delivered in your template under your brand, ready for whoever builds the quantum.
What you receive
The measuring starts from a clean sheet instead of a sorting job: one dataset, every line traceable, structured to the case you intend to run and delivered under your brand. The method note alongside grades every source and period honestly, so you know before a figure is claimed which records are reliable and which are not yet.
The Handover Pack accompanies the work with its dates and sources, likely outcomes and responses, scope boundaries and ready-to-send correspondence where needed.
Turnaround: the timetable is agreed in writing at scoping and then kept.
The working days start when the agreed scope and required inputs are available. Optional items do not hold the start unless the agreed scope says otherwise.
How it works
You tell me the heads the data must serve
One call on the claim: the heads you intend to run, the period they cover and the format the dataset must land in.
I clear conflicts and scope the work
I check parties and projects against my other engagements before I open a file, then confirm the heads, sources and format with you in a short written scope.
You send me the paperwork
You send everything below as it comes, straight off the job; unreconciled and duplicated is expected.
- A
The raw records in whatever form they exist
EssentialWithout it: There is nothing to organise, so the job cannot start
Where to find it: The accounts system's exports, the commercial folders and the site's returns
Why I need it: The whole set is needed to see the shape of it, and a sample hides the inconsistencies
- B
The issue, in their words
EssentialWithout it: The dataset risks being built to answer the wrong question
Where to find it: This is not written down anywhere for me to find. A paragraph from you, in an email or on a call, is what I need
Why I need it: The structure follows the question
- C
The deadline
OptionalWithout it: The dataset gets built without knowing how much structure is worth the effort
Where to find it: Whatever correspondence or instruction set the date, or your own diary if nothing about it is written down
Why I need it: Determines how much structure is worth building
- D
Whoever created the records, for half an hour
ImportantWithout it: The interpretation rules behind the dataset are guesses rather than confirmed conventions
Where to find it: Not a document at all: half an hour on a call with whoever in your team actually filled the records in
Why I need it: Interpretation rules are guesses without them
Copies are fine. Send what you have and I'll tell you what's missing. Download the client request PDF or editable Word version to pass to whoever holds the files.
Structure Agreed in Writing
The dataset's fields, units and conventions are confirmed with you in writing before extraction starts, so the work lands in a shape your team can use.
- A
I grade the quality before building
Every source and period is graded complete, partial or unreliable, in writing, before anything is built on it. Weak data is named early, with the records that would close the gaps, while the decision about what the dataset should cover is still cheap.
Quality Graded Honestly
Every source and period is graded complete, partial or unreliable in writing before anything is built on it, so weak data is named early, not found late.
I reconcile the sources
I strip duplicates, resolve rival versions against the records, and leave one set of figures standing, with what survived and why stated.
I build the dataset
I date every cost line, allocate it to its head and trace it to the document it rests on, in native Excel that shows its workings.
Totals Reconcile Exactly
Nothing is delivered until rows in, less exclusions, plus corrections equals the delivered dataset to the row, so every line is accounted for.
You decide which gaps get chased
The quality grading names the records still missing; whether each gap is worth the chase is your call.
I hand over one dataset, every line traceable
Free Service Pack
A step-by-step Handbook, with the templates and working documents you need to carry out the work it covers yourself. You supply your own project information and records.
Follow the Handbook's scope and stopping points, and obtain independent advice where required. The pack is not project-specific advice or independent sign-off.