Possibly the most over-worked, under-funded resources in any large enterprise are those responsible for Knowledge Management. Often with multiple data repositories and millions of files under their jurisdiction, KM professionals must analyze, search and retrieve complex content on demand. Such data requests often present a formidable challenge without strong tagging, taxonomies and management controls, such that users typically cannot self-serve and add to the KM team’s burden.
AutoClassification is changing all that, with the ability to richly tag content across many different dimensions and facets, while still respecting a well-honed taxonomy. Feeling confident? You might be ready for a demo!
1) Prepare. Locate and pre-tag stored content in advance
Crawl and tag content from disparate data sources across the entire organization; from shared drives and cloud storage environments to third party repositories, even legacy scanned paper files. Baseline tag all content for key attributes, such as: DocType, Product Names, Components, Keywords, Sources, Dates and Competitive Issues.
2) Enhance. Setup rules & attributes for easy retrieval
Enrich files with specific metadata tags related to purpose, location, age, business use, retention lifecycle, legal hold, and taxonomy. Build automated workflows around analysis; search and retrieval; reporting, and litigation and M&A requests. Ingest new content automatically, enrolling it in your taxonomy at the outset, with full metadata tagging from the get-go.
3) Query. Run searches, sorts & reports to deliver results on demand
Run consolidated searches, view reports, preview documents, and better mine your data and content populations against your search requests. Easy access and usage reporting helps justify ROI. Finally enable data requestors to self-serve!
4) Produce. Pull files, reports, job status & productions as needed
Respond quickly to any manner of search request, from product or components history, to intellectual property, to records cleanups and litigation. Create automated content pulls by time or cadence, by request type, by content arrival, by event or on command. Supplement content pulls with status reports and summaries.
5) Repeat. Automate data request processes and procedures.
Setup for regular, ongoing queries and ad hoc, on-demand ones. Build custom front-ends for ease of use and rapid request processing. Enable self-service with custom forms and built-in searches. Easy drag and drop plus web-based access. Plan request response time and resource allocation needs well in advance.
6) Monitor. Track performance, usage and results over time.
See real-time metrics tracking for performance analysis over time. Forecast future needs for resources, processing power and turn times. Consolidated data visualization supports metrics, access, and viewing from full corpus, to single searches, to individual files. Control your organization’s valuable content, including the searches operating across it.
Case Studies
See how Valora clients streamline Knowledge Management with AutoClassification:
eBook: 8 Pillars of Information Governance
Learn how each pillar helps build the foundation of a dynamic Information Governance Strategy…
Saving American History with PowerHouse
60,000 historic legal opinions urgently needed to be brought into compliance for storage, retention, tagging, and posterity…
Addressing GDPR and CCPA with AutoClassification
A large, casual, fast-food chain was specifically searching for a solution to emerging data privacy concerns…
Webinars
View our on-demand webinars on AutoClassification best practices:
PowerHouse AutoClassification
The world-class Machine Learning technology automatically determines document content, attributes & purpose,…
Data Minimization Examples
To help demonstrate good (and bad) practices regarding data minimization, we’ve gathered up a few real-world examples for you to consider.