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This is the second in a series of blog posts that will focus on answering the question “what is the long-term future of Jive?”


A few weeks ago, I shared a blog post that described the thinking and broad outline around how we see Jive evolving as a product over the next decade.


If you haven’t had a chance to read that first post – including the vital interaction with customers around it – I encourage you to do so.  But in quick sum, our vision for the future of Jive is based on the following premises:


  • Enterprise social networks, and the companies that created them, have largely failed on the original promise of leveraging the consumer social network to unlock real collaboration and productivity in the enterprise
  • This failure, we believe, is a function of a fundamental design flaw – neglecting to put people as the central structural principal of the enterprise social network – just as it is in the more successful consumer social network
  • As a result of this failure, most enterprise social networks ultimately crumble under their own weight from a phenomenon called “digital crowding…”  which occurs when the noise in the system overwhelms the signal, making the whole useless
  • This leads to churn – as users seek out a new network that is less crowded until that one in turn is overrun; “Slacklash” is just the latest example



Our future vision for Jive is to re-establish people as the critical center of the enterprise social network – and by doing so, create a much more meaningful, relevant, and valuable environment for enterprise connection, discovery, and collaboration.


In this post, I’ll dig a bit deeper into the technology that will power all of this – a technology we call “PeopleGraph.”  Fair warning – I’m going to talk in abstract as opposed to specific terms in order to communicate the general concept and broad capabilities of PeopleGraph.  This may be frustrating, as the specific capabilities enabled by PeopleGraph are going to get relatively light treatment here.  In future blogs, I promise to share more specifics on the use cases that PeopleGraph uniquely enables and those that are on the short-term and long-term roadmap, and why we believe it will be so transformational.  But let’s start by explaining what we’re talking about here.


PeopleGraph is the technology by which the new Jive will understand and assign a value to the relationships between people in an organization.  It is built on a powerful graph database (Amazon Neptune) – a data structure uniquely suited to representing people relationships.


To be sure, consumer social networks have leveraged network/graph technologies for years.  But, to our knowledge, no one has yet attempted to create a graph structure with the richness of relationship representation envisioned by PeopleGraph.


PeopleGraph will bring five fundamental dimensions to the table that are new – to Jive, yes, but also to social network technology in general.


PeopleGraph will understand not just connections, but connection types.


If you think about every social network you’re familiar with – including Jive – they all basically understand one single connection type – Twitter followers, LinkedIn connections, Facebook friends.


While it’s not reflected on much anymore, it is patently absurd that a social network understands only one kind of connection.



PeopleGraph will understand the myriad relationships we all have – some of which we are defining now as part of the first implementation of PeopleGraph, and some of which we expect to define over time as we work with customers and understand other valuable relationship types that it will be useful for PeopleGraph to be able to represent. 


PeopleGraph will know how you are connected in the formal organizational structure.  That is, it won’t be just a graphical representation of the organizational hierarchy (as is the case with Jive today).  PeopleGraph will understand and be able to represent the entirety of the enterprise organization and reporting relationships.


It will also understand that other, non-organizational relationships are just as relevant, and that there are many different types of those – relationships like mentor/mentee, team member, friend, subject matter expert, and many more.  And that the kinds of content sharing and collaboration that is appropriate or useful for those different types of relationships can - and often will - be different.



PeopleGraph will have a rich conception of individuals and will be able to translate that understanding into an even deeper understanding of connections.


PeopleGraph will enrich its understanding of people via integrations with HRIS systems, Microsoft Active Directory, LinkedIn, and other sources.  And it will use this information to develop detailed profiles of people – their work experience, skills, education, etc. – to further inform the nature of connections.


Ultimatlely, PeopleGraph will also interpret the content that people produce or consume – content natively produced in Jive but also, optionally, content produced or consumed in email, messaging applications like Slack, or document collaboration applications like O365 or Google Docs. 


This will yield additional insights about an individual - such as the topics of interest, or those for which they are considered credible sources of insight (as an aside, I recently came across a fascinating and analogous discussion in the publishing community about beginning to more deeply integrate reader contributions as part of the story, and the need to discern credible contributors from random noise).


All of this deep people insight – coupled with an understanding of the different types of connections people within an organization can have – will enable Jive to create an experience for each user that is uniquely personalized, and provide the ability to narrow or broaden the information aperture of a conversation (stay in the “VIP section” of the concert or head into the crowds – or go back and forth between both).  It will also create an incredible, powerful search experience and enable Jive to serve up, at the appropriate time, relevant people or content recommendations based on the context of the work people are doing in Jive.


I recognize this is all described conceptually at this point, and I’ll be presenting more specific use case examples in future blog posts on the three core value propositions of the future Jive – connection, discovery, and collaboration.


But let me give one specific example.  Many customers use Jive for CEO level interactions with the broader employee base – something we regularly do at Aurea as well.  These posts can often generate hundreds of comments with wide ranging topic threads (in fact, my original post on AureaWorks on this topic fits in this category).


You can imagine a reader “dialing up” or “dialing down” a view of the dialogue based on numerous attributes – the credibility of the contributors on that particular topic, seniority, tenure, organization, location, skills, expertise, relationships types, etc.  It’s nothing short of controlling “digital crowding” – the ability to manage the environment to suit the need.


PeopleGraph will understand different connection strengths.


In addition to connection “types”, PeopleGraph will also understand connection “strengths”, or how deeply different people in the organization engage with one another.  This could be direct engagement, such as active collaboration or communication, or indirect engagement, such as consuming or otherwise engaging with someone else’s content.  In either case, over time PeopleGraph will begin to understand your “expressed” network of stronger relationships, based on who you spend time with (from your calendar), who you interact with (from email to chat to Jive itself), and whose content you consume.


PeopleGraph will identify latent relationships of value – generally and contextually.


All of this information – the connection types and strengths, the people attributes, the affinities between people and the credibility they establish with each other – will be represented via the PeopleGraph.  And because all of those things are represented in graph technology through connections, Jive will be able to ask PeopleGraph to traverse those connections to identify relationships, affinities, or points of connection between people that are potentially useful, even if (perhaps especially if) those people do not know each other today.


This will be useful in search, of course.  But it will also be useful in the context of collaboration, content consumption and creation.  Imagine a scenario where a person creating or reviewing a piece of content is given suggestions for other pieces of relevant content, or other people who might be useful contributors or reviewers – or who have created similar content in the past.  All of these connections will exist in - and come to life with - PeopleGraph.


PeopleGraph will present Community Leaders with unprecedented insight into the connection points and collaboration patterns within their organization.


Giving administrators insight and control is an essential part of fostering a healthy community.  No community, left entirely to its own organic development, will be as successful as one that combines organic growth with effective stewardship from a talented community leader.


Our expectation is that PeopleGraph will enable a level of insight and control that goes well beyond the traditional usage and activity metrics that Jive and other platforms have historically offered.  While we haven’t gone so far as to spec any of this out yet, I can give you an idea of what is theoretically possible - given the information that will be available within the PeopleGraph structure.


In addition to understanding user activity, Community Managers will be able to understand the evolution of organizational dynamics and relationships.  They will be able to see patterns of connection, and where organizational knowledge is being siloed. They will understand the impacts of churn on things like “brain drain,” and they will understand how skill and “expertise density” is evolving over time in their organization.


They will be able to compare the theoretical knowledge and collaboration potential of their organization relative to that which is actually being expressed in Jive, and understand what explains the difference.  In short, we should be able to move from “community management” to “human capital and knowledge management.” A lofty ambition for sure, but one which is at least theoretically possible through the data available to Jive in PeopleGraph.


The user experience – Connection, Discovery & Collaboration


In the next three blog posts in this series (and I’m committed to getting all of them out prior to the first Aurea Experience ’18 in Munich this November), I’ll delve a bit more into how we see PeopleGraph enabling what we’ve defined as the three primary value propositions of Jive – connection, discovery, and collaboration.



Until then, I look forward to your feedback and advice.  All of us at Aurea are genuinely excited about the future we’re working on building for you.  We appreciate your patience, and your tolerance for the disruption that comes with change, while we architect this future.  I’m 100% convinced it will be worth it in the end.

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