First, give conclusions that can be used for decision-making
“Data bad” is not a reason to stop all AI work, nor an excuse to skip governance. Businesses should narrow the problem down to specific tasks, taking stock of the knowledge, structured data and historical samples needed.
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.
Suggested order of advance
First, we'll be clear about the target and the border.
Identify an operational task with high frequency and results to be reconciled.
Validation Key Dependence
(b) Inventory of data, gaps, authority and quality issues required for the task.
Development of assessable outcomes
A manual baseline was established and controlled PoC was completed with small samples.
Make sure you decide the next step with the real results.
Reinserting data, reprocessing processes or adjusting scenes based on failure classification.
How do you understand it in the actual business?
Instead of being an open business assistant, the firm can first choose to generate sales weekly reports, and fix the calibration of confirmed orders and returns; and gradually repair the client’s master data while at the same time verifying value. The examples do not represent the performance of a particular client, and the actual conclusions need to be verified in conjunction with the enterprise’s own business volume, sample, system and liability boundaries.
The easiest pit to step on.
It was felt that the entire company data governance had to be completed before the pilot could be implemented.
Hand unrecognized historical data over directly to the model
Only adjust the hints when data problems arise, without correcting the source process
How should we end up receiving and confirming?
The first issue of the scene data inventory, sources and responsibilities, quality baselines, authorizations, samples and gaps management options should be delivered; the PoC report needs to distinguish between modelling and data issues and to describe governance matters that must be completed before production goes online.
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.