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4 Posts authored by: sbrighton Employee

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

 

In this blog post, I'll continue exploring the future of Jive - a future based on a core technology we call PeopleGraph.

 

For those of you who joined us in Munich or New Orleans for Aurea Experience '18, I want to thank you for your time and your feedback, both on the tactical issues we're wrestling through and the future direction we're building toward.  Broadly speaking, I'd summarize that feedback in two camps. On the tactical front: "You are making progress but nowhere near fast enough - we still have too many issues." And on the future direction: "This sounds great - we want to see you deliver."  Fair enough, and I agree on both counts.

 

This series is focused on the latter part, helping to shed light on what we're working on as we look to reinvent Jive for the next decade of category leadership.  As a refresher, our core thesis is that enterprise collaboration has not delivered on its original promise principally because there has been too much focus on content creation (more and more tools for people to create more and more content) and too little focus on people (relationships, connections, expertise/skills, and the content they create and consume).

 

The result is "digital crowding," an explosion in enterprise content that has crowded out meaningful, purposeful, and valuable collaboration and knowledge sharing.  What's more troubling is that this situation is only going to get worse.  We are in an era of exploding content creation tools (estimates suggest that as much as 90% of all web content has been created in just the last two years).  Add in increasing organizational complexity - globalization, virtualization, and the emergence of the "gig economy" work force - and it's not hard to see how collaboration tools built for chatter (thank you, Salesforce, for naming your product after the problem) are ill suited for this organizationally complex and distractingly noisy collaboration landscape of the future.

 

In prior posts in this series I mentioned the three core capabilities that PeopleGraph is designed to enable: Connection, Discovery, and Collaboration (there is also a fourth- "Insights" - but as that is Community Manager focused as opposed to user-focused we will handle that in a separate series).  In the last post, we talked about Discovery and how PeopleGraph will enable an unprecedented level of people and knowledge discovery through its ability to richly understand people, their relationships, the content they create and consume and the work they do.  In this post, I'm going to focus on Connection.

 

Enabling Connection with PeopleGraph:  The Richest Representation of Your Organization

 

Connection is going to be a new concept in Jive, so before I dive into some of the specific capabilities it will offer, it's worth spending a few moments coming back to PeopleGraph and one of its important design principles.  This will, I hope, help clarify why we believe the new value offered by Connection is so fundamental - and so significant.

 

I've described PeopleGraph as the future core engine of Jive.  And that is true, but the fact of the matter is it has been designed and implemented to be much more than that.  Our ambition for what PeopleGraph can do is not limited by the current bounds of Jive.  The design mandate of PeopleGraph is to be the single richest source of people insight about an organization that exists within the enterprise.  As such, it is being architected to ingest and represent information about people from a vast array of applications where people either do their work (e.g., Google Docs) or represent important information about themselves (e.g., LinkedIn).

 

PeopleGraph has been designed to pull insights and information from myriad sources including Office 365, Google, email, calendar, and LinkedIn (where, ironically, the organization can now 'take back' employee data that LinkedIn is in effect using to help pilfer organizational talent).  Future sources will also include Box, Salesforce, HR systems, and (of course) Jive itself.  In total, the depth of insight PeopleGraph will have about people and their relationships will be deeper than any other source in the enterprise.

 

Given this depth of insight, having the ability for users to inspect, navigate and enhance PeopleGraph's perspective is important.  This is the purpose of Connection - enabling full exploration and exposure of the deep people insights that PeopleGraph contains. And what will this mean for people and teams?  Newer, broader and more meaningful organizational connections that create heretofore untapped opportunity for valuable collaboration.

 

Visualizing and Cultivating Connections

 

One powerful aspect of what Connection will provide is the ability to visualize your connections, much like LinkedIn or other public social networks enable you to see all of your different connections.  Like LinkedIn, users will be able to see the basis of their connection with other people in the organization that they may not have a formal relationship with (LinkedIn's notion of second and third degree connections).  But that's really where the similarities end.

 

Recall that there are three core types of connections that PeopleGraph recognizes: organizational relationships, explicit relationships, and implicit relationships.  Connection will enable you to visualize and navigate all three.

 

Organizational Connections

 

Organizational connections will be visible in the standard organizational chart, enabling users to jump from the org chart to an individual within it or jump from the individual to their place within the org chart.  Like Google Earth, users will be able to visualize the org chart at different levels of granularity and at different distances, "surfing" in a way that enables an effortless search and browse experience.  There have been organizational chart navigation experiences before, but never one quite like this.

 

 

Explicit Connections

 

One level beyond the organization chart are explicit relationships: the network people build within the company.  This enables people to reflect each user's networks - the people with whom they have established formal connections in the classic social network definition.  PeopleGraph will use its understanding of these connections to improve personalization, but also to more intelligently help people expand their networks in valuable ways.

 

The visualization of these explicit relationships will be more sophisticated than the simple lists that are de riguer for networks like LinkedIn or Facebook.  Relationships can be grouped, filtered, or sorted across numerous dimensions, including geography, function, title/level, tenure, skills, experience, expertise, and relationship strength, among others.  One's network is no longer just a list of people, it is a work asset that can be inspected, analyzed, and ultimately leveraged to get work done.

 

 

Implicit Connections

 

One of the more interesting elements of PeopleGraph is its ability to reflect and understand attributes and relationships that aren't captured by the org chart or reflected in an individual's personally curated network.  The inspection of this network is among the most valuable elements of PeopleGraph, as the ability to leverage this understanding is key to how the future Jive eliminates digital crowding and will lead a reinvention of the enterprise collaboration space.

 

While we've yet to fully design the UI representation of these capabilities - most of the focus of the last several months has been on the core PeopleGraph data structure and inspection algorithms - we can share a general sense of our thinking on how users might "surf" the organization outside the more traditional context of the organizational chart.

 

We expect to create a search and browse-based experience that closely mirrors the shopping experience: items (people) on the right that can be filtered and sorted by various criteria.  The best shopping sites act like divining rods on steroids, narrowing hundreds of thousands of SKUs to the few of relevance extraordinarily quickly.  We aspire to do the same with people.

 

Let's illustrate the use case with a specific example.  Assume a user is working on a project to launch a new consumer product in Poland.  The user, in this example, is leading the distribution strategy on behalf of your company.  She's been asked to put together her team for this important initiative.

 

In the future, she will go to Jive, and - rather than surf the organization chart - she will surf the PeopleGraph.

 

First, she selects people that speak Polish.  Then, she sub-selects people who have credible expertise in retail distribution (she could also select for people who claim expertise in retail distribution, but in this case she's using PeopleGraph's ability to discern validated expertise based on their validated work contributions).  She then sorts the resulting list of people by "relationship relevance," or people whom PeopleGraph discerns have the strongest connection to her (she might decide to do the opposite and find people with whom she has little connection, but in this case she is prioritizing relationship affinity as a predictor of team chemistry).

 

Satisfied she has the right person, she looks to turn this "implicit" connection into an "explicit" connection by requesting the latter in a manner that is familiar to most users of social networks.  She then invites this person to a traditional Jive group collaboration session that enables to new invitee to quickly get up to speed on all the content and conversations on the project.

 

 

In effect, what PeopleGraph will enable is "shopping for people," providing users the ability to identify resources in the organization with whom they can build relationships and strengthen their network and knowledge base.

 

We view this capability as the single most powerful and important source of value from PeopleGraph.  And it is important to understand that this is fundamentally different from a Jive profile search.

 

PeopleGraph builds its rich understanding of people from all the major sources of people knowledge within the organization - a scope of knowledge that goes well beyond Jive.  When a user is searching for a person that has a particular expertise, PeopleGraph will not identify people that have that expertise by a "dumb" profile search.  Rather, PeopleGraph will have assessed this expertise based on that person's content, contributions, and work across a rich variety of data sources (the aforementioned Office 365, Google, LinkedIn, email, calendar, and others).  This is real, demonstrated expertise and content and not a function of who spends more time building their profile.

 

Transforming Enterprise Collaboration

 

Honestly - and humbly - we believe this is going to transform organizations and work at the same level that Jive did originally back in the first decade of this millennium.  Jive invented enterprise collaboration - and it changed everything.  We are now committed to reinventing it.  Organizational complexity and an explosion of content have reduced the effectiveness of existing collaboration solutions; digital crowding has become a plague on the entire space.  So while every other collaboration solution focuses on helping people create yet more content, Jive will be focused on creating the richest and most complete representation of people in your organization.  That representation will make everything about collaboration more powerful.  Jive will simultaneously become broader (by enabling connections between people that would have never connected before) and more focused (by narrowing content presentation that that which is the most relevant).

 

I have been intentionally vague in describing when these capabilities will start to see the light of day.  So let me make two commitments here:  first, you will see PeopleGraph-related deliveries before the end of 2019.  And second, the initial set of those capabilities will center around this innovation theme of Connection, in part because the inspection and cultivation of the PeopleGraph relationships are at the core of the new Jive and everything else we will do.  The first deliveries will be basic - we need to start with the basics - but will start to give you an immediate sense of where this is all going and how the future I've been describing in these blog posts will be made possible.

 

Thanks for taking the time to read these thoughts, and as always I look forward to your comments and feedback.

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

 

In this blog post, I’m going to start digging a bit deeper into the use case impacts of PeopleGraph.  As a quick refresher, PeopleGraph is the technology on which we are betting the future of Jive.  We began working on this roughly six months after acquisition, and in the last post in this series I provided a bit more detail on what PeopleGraph is and why we believe it is both important and transformative.

 

The key capabilities that PeopleGraph is designed to enable – Connection, Discovery, and Collaboration – are the topics of this and my next two blog posts.  As a finale, I’ll also be describing the powerful new “organizational insights” that Community Managers will be able to glean when our new reporting dashboard begins inquiring and inspecting PeopleGraph.

 

For this post, I’ll focus on Discovery.  Where possible, I’ll try to give guidance for things that are explicitly “on the roadmap” vs. those that are concepts still in the investigation phase.

 

The Most Basic Facet of Discovery:  Search

 

Search has always been a key feature of Jive and of most enterprise social networking, content management, and interactive intranet solutions.  Irrespective of how they use Jive, I have yet to talk to customers that have not cited search as a critical capability – and an area where they would like to see significant innovation and product improvement.

 

Search in Jive today is adequate – better than most of the competitive offerings, but  materially weaker than the consumer equivalents that are the basis for how most users will judge enterprise software today (comparing it to Google, for example).  This can generate a great deal of user frustration, and inadequate search in a content-rich enterprise portal can be one of the earliest and most important signals of the “digital crowding” problem I addressed in earlier posts.

 

Search in the enterprise is uniquely hard – which is why Google abandoned its search appliance and why search within Google docs is so much worse than Google web search.  Techniques that are so successful on the internet, such as Google’s PageRank, are significantly less effective in the enterprise because the things those algorithms depend on, such as backlinks, don’t exist in the enterprise content context.

 

This is where PeopleGraph comes in.  PeopleGraph enables us to replicate, in many ways, most of the relevancy and intent advantages that Google’s PageRank and successor algorithms have applied so successfully to the web.  At its core, PeopleGraph is a series of links; this is precisely why the same principles that Google uses to make decisions regarding user intent and search result relevancy can be applied by Jive search using PeopleGraph.  Jive will make decisions using the volume and strength of various connections between people and the content associated with those people.

 

The advantages of this go beyond just intent and relevancy.  Much as Google cannot manage the content of the Internet, the new PeopleGraph powered Jive search will not depend on a content managed enterprise ecosystem.  In theory, as the enterprise evolves and PeopleGraph reflects that evolution, the links and strengths of links between people and the content they are associated with will change.  Those changes will alter search results, such that “old” content becomes less relevant as the links to it weaken both in number and in strength.

 

Let’s dig into a specific example.  In this scenario, let’s assume that Jan is looking for information on Amazon Web Services, and specifically the Amazon Web Services migration plan.  If you were to run such a search in Jive today, you might type “Amazon Web Services migration plan” yielding (in our own Aurea51 instance) the following results:

 

 

 

Two problems are immediately apparent.  First, people routinely refer to “Amazon Web Services” as “AWS,” and because Jive search does not understand that these are the same thing, those entries are all missing from the search results.  This is a problem of intent – the old Jive search has no understanding of your intent here.

 

The second problem is that the old Jive search (and most enterprise search) will bias to older documents precisely because they are old.  The newer content with the most relevant information on the migration schedule is lower on the list.

 

With PeopleGraph powered search things will be different.  Let’s take a look at the results of the same search when run on PeopleGraph.

 

 

You’ll notice a few things almost immediately.  First, the bulk of the results reference “AWS” – Jive search now understands this to be the same as “Amazon Web Services” and, it turns out, most people refer to it that way.  This “intent” engine will also help with common situations such as name misspellings or common words that can be spelled differently (i.e. organization vs. organisation). With PeopleGraph, intent can be inferred.

 

Second, you’ll notice that the nature of the results are different with a significant emphasis on more recent content.  This is almost certainly because the link strength to this content is very strong, despite its recency, because of the people who created it or are consuming it.  Jive search can understand the strength and breadth of these links as a good indication that this is a substantive, definitive document.

 

Finally, you’ll notice the search now even includes people, despite the fact that we are searching for what is obviously not a person.  PeopleGraph enables Jive search to identify experts on the particular topic – in this specific case the person who is [TS4] accountable for the AWS migration plan.  The searcher can use this additional information to go “right to the source” – either directly or by starting a group that includes that person.  This is obviously a use case that makes little sense in the internet context but can be extraordinarily powerful for the enterprise.

 

Passive Discovery:  Contextualized Suggestions

 

A completely new element of discovery that PeopleGraph will enable is something we are calling “contextualized suggestions.”  The general concept is not terribly different from how consumer browsing or shopping applications provide suggestions for other content or products that you may be interested in based on the content (or product) you are currently engaging with.  The difference here, though, is that in addition to recommending content, PeopleGraph will suggest people in context whom it would be valuable to engage with around the content in question.

 

Let’s look at an illustration on how this will work.  In the example below, you will see that the individual user is involved in a group discussion on a document about a supply chain proposal written in the programming language Python that is  for a French speaking customer called Roederer. In this example leveraging PeopleGraph, you will notice now that the document being viewed is now making several “suggestions” – both people suggestions and content suggestions.

 

The people suggestions are folks within the organization that PeopleGraph has identified as experts on the discussion topic in question.  The content suggestions, similarly, are related documents whose content might inform the discussion.

 

In this example, let’s assume that Marcia (the user) is interested in possibly involving some of the identified experts to further inform the discussion.  She clicks on Jimmy to understand who he is and the nature of his inferred expertise.

 

 

We notice that Jimmy is among the highest rated resources in the company on python, and furthermore he has created several pieces of content that are highly related to the document being discussed in the group.  Marcia can invite him to participate in the group, and Jive can immediately provide the context as part of the invitation.

 



A Long-Term Future of PeopleGraph-Powered Discovery

 

Better search and contextual suggestions are straightforward applications of PeopleGraph for discovery, and ones we expect to deliver early in our roadmap once PeopleGraph is deployed.  Over time, though, one can imagine additional possibilities.

 

PeopleGraph is being architected as a service external to Jive, and will include a robust API (integration) layer to make it easy to connect with Jive and other critical data sources – HR systems, Active Directory, Office 365, Slack, Box, Salesforce, etc.  Every source that PeopleGraph connects to will enrich PeopleGraph’s understanding of the organization.  This means that, long-term, PeopleGraph can understand:

 

  • The content associated with Slack or other transient messaging applications, enabling that to inform search as well as PeopleGraph’s understanding of organizational relationships
  • Connections to people outside the walls of the enterprise, such as customer relationships as mastered in Salesforce and how those relationship strengths manifest themselves in the company context (how strong is our company’s relationship with Apple, and what are the specific relationships we have and who has them?)
  • Content associations for documents stored outside of Jive, ultimately enabling search to find people or content that is not exclusively informed by what is resident within the walls of Jive

 

We believe PeopleGraph will drive a profound change in people and content discovery – initially within Jive but over time, increasingly drawing from the ecosystem that surrounds it.  Over the weeks and months ahead, we will be releasing demo videos of the prototypes in action to give you a real sense of how this will work and the progress we are making on it.

 

As always, I invite your feedback and questions.  Thanks for taking the time to engage in this discussion with us.

 


 





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.

Latest on the Series:

The Long-Term Future of Jive (Episode Two)

The Long-Term Future of Jive (Episode One)

 

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

 

The “long-term” part of that question is important and warrants a bit of further definition.

 

When I say long-term, what I mean is product decisions and work that are durable – that we could live with ten years from now and still be building upon.  Decisions that will provide a foundation for multi-year future innovation, some of which we can’t even foresee today.  What I won’t be talking about in these posts are some of the tactical features or issues (as interesting as they may be to many of you) that are the focus of our very near-term releases. Of course, we’re happy to engage on those topics separately.

 

Customers are rightly thirsting for transformative innovation.  The collaboration space in particular is rife with “new stuff” that can create a visceral sense that -- absent constant innovation -- your organization is somehow falling behind.

 

But we believe much of the “innovation” happening in collaboration is simply recycling of old ideas – the resurgence of chat as the hot new category is a primary example of this. In contrast, we have been looking for ways to create more profound impact … something that resets Jive on a true leadership path to drive differentiated value in ways that other enterprise collaboration solutions aren’t pursing.

 

An essential part of doing this involves rethinking what Jive is from the ground up.  The most important part of any construction project is the foundation and structural design.  Over the past year, we’ve been working intensively on designing and building this new foundation.  This work is not particularly visible to you, but it’s vital if we’re to reinvigorate this product and this company.  In effect, we’ve been rethinking – and rebuilding – the very core of Jive.

 

So, in the spirit of working out loud, I’ll share with you what we’ve been working on and, perhaps equally as important, why.  In all of this, I’m interested in your candid feedback.  Much of this we haven’t shared as yet, even with our Customer Advisory Board.

 

The Enterprise Social Network

 

As we began this work - roughly 100 days after acquisition - one of the first questions we needed a good answer to was why Jive had struggled – why its growth had stalled, and why its investors lost faith and decided to sell the company to us.  We began by tracing the steps backwards from the very beginning.

 

2008 can be considered the year enterprise social in its modern form was born.  This is the year that a group of startups – Jive, Yammer, Chatter, Mzinga, Dekks, and others – emerged with the aspiration of taking the Web 2.0 social revolution into the enterprise.  Ambitiously called “Enterprise 2.0” – the idea was to unlock the same kind of frictionless, freeform connection and interaction that public social networks had enabled, but within the enterprise ecosystem to improve worker productivity.

 

Ten years later, the reality simply didn’t live up to the initial vision and hype.  Almost all the players – after a period of flourish and growth – saw that growth seize up.  Some, like Jive and Yammer, were acquired.  Others shifted their focus to ancillary markets.  Some have had their position deprecated to near irrelevance as part of a broader suite.  None emerged to become the Facebook or LinkedIn of the enterprise.

 

This is curious.  In the consumer world – where the temporal judgements of fashion would seem to put much greater risk on a social network’s long-term viability – things have been remarkably stable.  The big players – Facebook and LinkedIn – have proven durable and have driven enormous societal change over nearly two decades.  Why hasn’t one of the enterprise players emerged to have the same broad impact and durability?  Why isn’t Jive as big as Facebook?

 

We have a theory.  And that theory is the basis of our future vision and fundamental redesign of the core of Jive.

 

The Fatal Flaw of Enterprise Social

 

Social networking really involved two concepts.  “Social” – the ability to communicate and share content, and “network” –the ability to establish, maintain, and manage relationships.  Both have been important to the success of Facebook and LinkedIn, but our observation is the latter – the concept of network – is far more important and foundational than the former.

 

Looking back at each of their erstwhile competitors – mySpace and Spoke respectively – both of those players de-emphasized networking in favor of content.  As a specific example, in mySpace, your friends were anonymous.  A compelling case can be made that the simple ability to see your “real” friends in Facebook was the killer feature that enabled it to win.Our observation is that all of the “enterprise social networks” focused on content over networks and people. In fact, the industry would shortly thereafter avoid the “enterprise social software” moniker and adopt much narrower definitions – like “interactive intranet,” Importantly, Jive itself doesn’t even have the notion of a people network built into its core data structures; it assumes the entire company is your network (or, perhaps more correctly, that there is no network). Everything is built around content.  This is the case with, to varying degrees, every enterprise social platform we've evaluated.

 

So what’s the problem? Clearly, many of you (and even a handful of other enterprise social software product customers) have used the software to create transformative change.  The focus on content and collaboration has enabled a level of transparency and knowledge sharing that wasn’t possible before.

 

But we believe that social networks that aren’t grounded in people (the most important asset of a company) are ultimately undermined by a core problem – what has been referred to in academic literature as “digital crowding.”  This is the moment when the signal-to-noise ratio starts to go sideways, and the massive amount of unbridled content becomes chaotic and overwhelms the utility of the system.  Newsfeeds become overrun with irrelevant content.  Search becomes impossible.  Inboxes are stuffed with alerts.  Groups proliferate to the point of meaninglessness.  This chaos results in a wealth of content, but a poverty of attention.

 

The reason some Jive customers have been very successful is because of exceptional community management.  Great community management can help mitigate some of the impacts of “digital crowding” – you can almost think of it like crowd control.  But it doesn’t fully eliminate the effects; only a technology grounded in people can do that.

 

People generally respond to digital crowding by finding a new “less crowded” neighborhood (in this context, a new tool), and the cycle again repeats until that network is also overwhelmed. The much publicized “Slacklash” impacting larger Slack communities is merely the latest manifestation of this problem.  All enterprise social software companies suffer from poor retention, and our contention is that it is this very phenomenon that drives a constant search for something new.

 

An Enterprise Community Centered on People

 

Both Facebook and LinkedIn are, at their core, people networks.  Facebook “friends” and LinkedIn “connections” are the basis for every other experience on those platforms.  That basis helps makes the social aspect of those platforms more manageable, reducing the fatigue associated with digital crowding.  Note, though, that that the rather simple relationship representations that Facebook and LinkedIn are capable of understanding (everyone is a “friend” or not, and everyone is a “connection” or not) pale in comparison to what is possible now using cutting edge technology.  I’ll have more on this in a future post.

 

Which takes us to the new Jive. Our plan is to build the future of Jive around a technology we are building called PeopleGraph – an incredibly rich data structure and engine that will enable Jive to understand your company’s people relationships at an unprecedented level of sophistication. Not just better than what enterprise social networks can do, but also far beyond that which either Facebook or LinkedIn are capable of understanding.

 

Jive will understand organizational relationships – how people are connected via your company’s org chart.  Jive will understand various types of personal and professional relationships that aren’t simple and hierarchical – and extend out to friends, team members, colleagues, or mentors/mentees, and Jive will understand the relative strength of those relationship - which are important and which are less so.  Jive will also understand latent relationships – commonalities between people in the organization based on more subtle skills or work activities that may not yet be expressed as a formal relationship.  If there is any basis of connection between people within a company, Jive will understand it, its fundamental nature, and its strength.

 

As you can probably imagine, enriched with this kind of intelligence, everything about the Jive you know today becomes instantly (and in many ways transformatively) better. Search is an obvious example. With a deep understanding of people relationships, locating people within the organization based on skills or work activities will be trivial.  And, because Jive understands you, what you work on, and who you work on it with, its ability to help you discover content informed by those connections will be completely new.  The search experience that PeopleGraph will unlock for Jive will, at the risk of modest hyperbole, blow traditional Google semantic search out of the water.

 

But even more exciting are the new kinds of capabilities this unlocks that simply weren’t possible with the content-centric data structures of the old Jive.  We’re going to be getting into some of these examples in future blog posts (and showing some demos at Aurea Experience 18), but I’m sure you can imagine some of them already.

 

A Bold New World

 

We’ve been hard at work building this new core for Jive for the last nine months or so.  It is based on cutting edge graph database technology from Amazon and makes optimal use of the AWS technology stack.  It is designed for massive scale and supports the kind of rich relationship representation – different types of relationships and different strengths of relationships – that no social software today is capable of understanding.  It is a massively powerful and differentiated asset, and we believe it will re-establish Jive as the leader in organizational collaboration.

 

I’m over 1,000 words, so this is probably a good place to pause my thoughts and start the conversation. I’m anxious to hear your reactions, ideas, advice, and concerns.

 

I’ll be posting subsequent blogs on this topic every 2-3 weeks.  I’m excited to share our thinking, and I appreciate you taking the time to work out loud with us.

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