You Can Have Your Cake and Eat It Too! (Part Three)

As I promised in my last blog, I will discuss real-world examples of hybrid search deployment projects at both a large, publicly-traded manufacturing company and a well-known multi-national law firm.

First, let’s look at the manufacturing company and understand a bit about their systems. Their business productivity stack is Microsoft O365, and all business records are kept in OpenText. Their intranet is based on Salesforce Communities, and the organization also heavily uses Confluence and Jira.

The company’s OpenText contains over twenty million documents, with Confluence and Jira containing over one million objects each. Salesforce Communities has over a million items, and O365 contains over three hundred million items. Yes, that’s right. Three hundred million.

When you start thinking about the volume of potential content kept in SharePoint Online, OneDrive, and e-mail; scores of large enterprises will have O365 environments with over three hundred million items. Some with even more than a billion.

For the manufacturing company, Upland BA Insight recommended indexing OpenText, Confluence, and Salesforce into Azure Cognitive Search. With Microsoft O365, however, we recommended query-time federation leveraging SmartHub, merging the two indexes. Although there are two indices behind the scenes, to the end users it is only one search box to find everything.

This scenario is ideal because if you attempted to index three hundred million items, then it would take months and it would be virtually impossible to keep up with the rate of incremental changes. Search results would become stale. There is also a serious risk of not being able to find updated, relevant content. Just think of the legal and/or compliance exposure to an organization using outdated or incorrect information.

Let’s look at our final example of an *AM100 multi-national Law Firm.

This law firm has over 1,000 attorneys spread across dozens of offices around the globe. They have 60 million items (contracts, pleadings, motions, etc.) in iManage, a legal-based document management solution. Their intranet is based on SharePoint 2019. They use on-premises solutions for billing and client matter management.

All of these applications are mission critical. Due to the high volume and frequency of content changes in iManage, and in order to ensure content is fresh, query-time makes the most sense for these applications. On the other hand, indexing makes the most sense for their on-premises billing and client matter management applications.

Using a hybrid strategy for the firm was the best choice. They have one place to go to find everything. Content is fresh and relevant. They can easily repurpose intellectual property. The result is happy paralegals and attorneys, resulting in increased productivity.

To wrap things up, I discussed in this blog series how both types of federation, query-time merging and index-time merging, are powerful tools for enterprise search. It does not have to be one versus the other. Like the dinosaur, that type of thinking should be extinct. There are times when indexing content makes the most sense. However, frequently for complex enterprise environments, the hybrid, multi-index strategy tends to be the best solution.

So yes, you can have the best of both worlds.

Thanks for reading!

* The American Lawyer’s annual ranking of the 100 highest-grossing law firms in the country.