After Migrating, Consider: Wrapping Up a Migration
Several enterprise market dynamics have converged to create a new wave of conversational collaboration apps and services that offer compelling new opportunities to streamline work and get more value from enterprise content resources. This new wave is currently disrupting the traditional content/collaboration competitive landscape and creating new requirements for content/collaboration migration solutions. This post provides an overview of the emerging developments.
Clear Conversational Collaboration Convergence
There has been a significant shift toward conversational collaboration over the last year. The conversational user experience model, popularized by consumer-oriented activity stream-based services such as Facebook, is now gaining broad market momentum, with:
- Facebook adapting its news feed and conversational capabilities for organizational communication/collaboration scenarios in its new Workplace and Work Chat apps
- Google’s new conversation-centered Hangouts Chat app, unveiled at its Cloud Next 2017 conference
- IBM’s introduction of the next version of Connections (code-named “Pink”) at its Connect 2017 conference, with new capabilities such as Live Grid (making it possible to work with structured lists in conversational contexts) and integration with Watson Work services
- Microsoft’s introduction of Teams in early November 2016, which came as a surprise to a lot of people, especially those who had attended Microsoft Ignite 2016 several weeks earlier and had assumed SharePoint was still Microsoft’s primary focus for team collaboration; Teams became generally available for all Office 365 customer organizations on March 14th and is likely to see brisk market uptake
- Slack expanding the scope of its enterprise-oriented capabilities with Slack Enterprise Grid and plans for new machine learning capabilities both developed on its own and delivered in a Watson partnership with IBM
- Other key players focused on similar market dynamics including Atlassian, Jive, and Salesforce (with Chatter and Quip)
Why This is Happening Now
The shift to conversational collaboration can be traced back to the “enterprise social” wave which started more than a decade ago (Jive, for example, was founded in 2001, and the first release of IBM Connections was introduced in 2007) and perhaps peaked with Microsoft’s 2012 acquisition of Yammer. While some products associated with the enterprise social wave met with mixed results, several recent developments have aligned to accelerate and expand the conversational collaboration shift.
The most significant enabling dynamic is the strong user preference for conversational apps, exemplified by the success of Facebook among consumers and the rapid growth of Slack for organizational domains. Many people suffering from email fatigue have found the conversational approach to be much more effective and now seek to use related tools for both personal and work activities.
Another change contributing to the conversational wave is the ease with which related systems can be integrated with external services. Examples include monitoring social media services for updates, such as having a Twitter connector monitor for references to an enterprise brand, along with integration with line-of-business applications such as Salesforce and Dynamics CRM (e.g., to inform a sales group via a chat channel when a potential customer opportunity arises). This integration model makes it possible for people to handle more of their work activities without having to toggle between apps – they can stay focused on conversational contexts and seamlessly bring external resources into the conversations when useful.
The mainstream use of hypertext content is another key enabler for conversational systems. People who routinely share smartphone pictures via Facebook, for example, are likely to use similar sharing techniques at work (such as posting photos of meeting whiteboards in a project chat channel). The ability to include traditional document types (word processor, spreadsheet, and presentation graphics) in conversational contexts is also significant, both reducing the amount of app context-switching and making it easier to work with “single source of truth” copies of documents securely managed in the cloud (rather than, for example, sending copies of files as email message attachments).
Bots – essentially in-context apps with the ability to engage in structured conversations with external systems – provide another incentive to use conversational systems. This approach, popularized by consumer systems such as Facebook Messenger and start-ups such as Slack, can be used for scenarios ranging from help and training systems (e.g., helping new Slack and Teams users learn about app features) to querying and adding data to external enterprise systems without leaving a conversation. For example, people jointly working on a new sales opportunity might bring a Salesforce or Dynamics bot into a conversation to interactively retrieve customer account details while formulating a new sales proposal.
The enterprise shift to cloud platforms is another key enabler for conversational systems. The ability to integrate with identity, authentication, and authorization cloud infrastructure services, for example, simplifies administration and management. Indeed, in some cases conversational systems can be considered a new user experience option built on top of already-deployed communication, collaboration, and content apps and services. Microsoft Teams, for example, builds on SharePoint Online, Exchange Online, Skype for Business, and other Office 365 and Azure services, but Teams users don’t need to be aware of the underlying architecture.
The cloud platform shift also presents new opportunities for low- or no-code application development tools. Using the same underlying services and connectors, new tools such as Microsoft Flow and PowerApps make it possible for non-programmers to create collaborative applications that can be integrated into conversational contexts.
The rapid evolution of machine learning (also known as cognitive) techniques is another important enabler for conversational systems. While the conversational approach can reduce the amount of email used in an organization, it can also become very difficult to keep up with when working with multiple teams and channels. Instead of dealing with 200 email messages a day, for example, you may now be skimming 2,000 messages a day across a collection of chat conversations. Machine learning techniques can be used to automatically summarize and personalize notifications and channel views to help people stay focused on the resources and activities most relevant to their work needs.
Overall, the conversational collaboration shift represents an opportunity to have happier, more collaborative, and more productive workers while also better leveraging and controlling enterprise content resources.
A New Enterprise Collaboration Competitive Landscape
The shift to conversational collaboration has created enterprise opportunities for new entrants such as Slack and Workplace by Facebook. It has also revitalized competition among enterprise collaboration incumbents including Google, IBM, and Microsoft. All the leading enterprise competitors are now putting major emphasis on their respective conversational collaboration capabilities, and all are also aggressively investing in machine learning techniques.
These market dynamics are increasing enterprise migrations from earlier generations of content/collaboration platforms such as IBM Domino and Microsoft SharePoint Server. They’re also creating a strong incentive for enterprises to consolidate their content collections into conversation-capable platforms (e.g., consolidating files from file shares and the first wave of file sync/share services into their preferred cloud collaboration service).
The expanding requirements, in turn, are increasing the need for enterprise-scale migration tools that can work with multiple source and target system types. It’s not a simple “lift-and-shift” proposition, however. While it may be straightforward to migrate folders of files from legacy deployments to new cloud-based conversational collaboration services, there can be a lot of nuance with inconsistent source system storage and permission models, and there are often opportunities to significantly simplify and consolidate content management when shifting to cloud services.
When dealing with elaborative collaborative applications on legacy platforms such as Domino and SharePoint Server, there’s also a strategic opportunity to disaggregate, modernize, and recompose applications to better leverage new conversational platform capabilities. A complex legacy collaborative app built on Domino or SharePoint can often be refactored, simplified, and modernized for today’s cloud-based conversational collaboration environments.
How CASAHL Can Help
CASAHL can simplify and expedite multi-source migration to modern conversational collaboration platforms. Working with multiple content/collaboration source and target types, CASAHL starts with an assessment service that makes it easy for enterprises to fully understand their existing deployments (on-premises, cloud, or hybrid) and explore opportunities to consolidate and simplify their content and collaborative app portfolios. With a fact-based migration project plan created during the assessment phase, CASAHL next uses a highly automated and enterprise-scale migration engine to address the full range of content/collaboration modernization and migration needs. Please see our Dart Product Suite overview for more details about CASAHL’s unique migration solution, and feel free to contact us for more information.
