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QUESTION & ANSWER

AI Report Automation Data Readiness

At least prepare representative original files, field descriptions, formulae calibration, expected output, unusual samples and current manual steps. If the result is to be returned to an ERP, CRM or financial system, you must also provide interfaces, primary keys, status and permission rules. Do not provide only a clean template, which should include missing columns, repetitions, empty values, misformatting and historical versions.

Answer the question.

First, give conclusions that can be used for decision-making

The goal of the information preparation is to make the team understand where the data comes from, how they change, how they are calculated, where errors may occur and by whom. The enterprise should provide normal and unusual documents, fields and business explanations, matching relationships, manual judgement rules, outcome approvals, and upstream/downstream system conditions.

DECISION FACTORS

What conditions need to be identified before judgement is made?

The same question may have different answers under different business, data and project phases. It is suggested that the following conditions be checked and that the common findings on the web be incorporated into their own projects.

Completeness of different sources and historical versionsIs there a common calibre for the field formula and statistical cycleWhether the primary key matching, weighting and abnormality rules are clearWho will approve the results of the write-back and official release
ACTION STEPS

Suggested order of advance

01

First, we'll be clear about the target and the border.

Collection of recent real documents and at least three types of unusual samples.

02

Validation Key Dependence

Marks field sources, formulae, primary accountability systems and expected output.

03

Development of assessable outcomes

Record manual processing steps, time-consuming and common errors.

04

Make sure you decide the next step with the real results.

Establish a fixed sample, reconciliation rules and acceptance officer.

PRACTICAL EXAMPLE

How do you understand it in the actual business?

Example used to illustrate the method of judgement

If the “client name” is not consistent in the various departmental sales forms, the main data problem cannot be detected by providing a standard template. The historical aliases, client code and manual matching results should be prepared together, deciding whether to manage the master data or create maps in an automated manner.

COMMON RISKS

The easiest pit to step on.

Final statements only, no raw data

The formula calibration depends on the memory of a certain employee.

Ignore empty values duplicated and inter-period adjustments

ACCEPTANCE

How should we end up receiving and confirming?

Project information should be sufficient to reproduce current manual results and to identify acceptable errors, manual exceptions, reconciliations and data privileges.

When preparing to communicate with suppliers or internal teams, it is recommended that current processes, representative samples, existing systems, planning time and budget levels be brought. First, the unknown items are clearly marked, and then the decision is made to use diagnostics, PoC, fixed-range projects or ongoing research and development, which is usually more reliable than a direct demand for a price and duration without borders.

Your project conditions are different from the examples above?

Operational objectives, existing systems, sample and planned time could be collated before consultants could make preliminary judgements in relation to actual boundaries.

Associate project consultants