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Intervening in Collaboration Networks

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People Analytics

University of Pennsylvania

4.5 (3,160 ratings) | 69K Students Enrolled

Course 3 of 5 in the Business Analytics Specialization

People analytics is a data-driven approach to managing people at work. For the first time in history, business leaders can make decisions about their people based on deep analysis of data rather than the traditional methods of personal relationships, decision making based on experience, and risk avoidance. In this brand new course, three of Wharton’s top professors, all pioneers in the field of people analytics, will explore the state-of-the-art techniques used to recruit and retain great people, and demonstrate how these techniques are used at cutting-edge companies. They’ll explain how data and sophisticated analysis is brought to bear on people-related issues, such as recruiting, performance evaluation, leadership, hiring and promotion, job design, compensation, and collaboration. This course is an introduction to the theory of people analytics, and is not intended to prepare learners to perform complex talent management data analysis. By the end of this course, you’ll understand how and when hard data is used to make soft-skill decisions about hiring and talent development, so that you can position yourself as a strategic partner in your company’s talent management decisions. This course is intended to introduced you to Organizations flourish when the people who work in them flourish. Analytics can help make both happen. This course in People Analytics is designed to help you flourish in your career, too.

Skills You'll Learn

Talent Management, Analytics, Performance Management, Collaboration

Reviews

4.5 (3,160 ratings)

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ST

Mar 18, 2017

Real helpful course especially for individuals who are in HR field or interested in becoming a better leaders, team players. Professors incorporated data analytics into human talent management!

BC

Dec 15, 2017

Excellent course! I learned more about HR and staffing strategy from this single course than the Human Resource Management specialization from the other university program offered on Coursera.

From the lesson

Collaboration

In this module, you'll learn the basic principles behind using people analytics to improve collaboration between employees inside an organization so they can work together more successfully. You'll explore how data is used to describe, map, and evaluate collaboration networks, as well as how to intervene in collaboration networks to improve collaboration using examples from real-world companies. By the end of this module, you'll know how to deploy the tools and techniques of organizational network analysis to understand and improve collaboration patterns inside your organization to make your organization, and the people working within in it, more productive, effective, and successful.

Introduction to Professor Haas0:30

Basics of Collaboration5:05

Describing Collaboration Networks14:51

Mapping Collaboration Networks16:03

Evaluating Collaboration Networks10:32

Measuring Outcomes9:08

Intervening in Collaboration Networks18:49

Taught By

Cade Massey
Practice Professor
Martine Haas
Associate Professor of Management
Matthew Bidwell
Associate Professor of Management

Transcript

So at this point, we have some good insights into the building blocks

that we can use to describe collaboration that works.

We have learned how to map collaboration that works using survey methods or

possibly other kinds of data.

And we thought about how we can evaluate collaboration networks,

both by looking at those collaboration metrics or building blocks across

individuals to compare them over time, perhaps, and also by

connecting them to outcomes that we might care about such as individual performance.

So, now that we fought about how to evaluate in that works

we can move to that final stage in our last segment,

which is to think about how to intervening in collaboration that works right?

How can we actually make a difference we can see, we can map, we can evaluate,

we can understand them that works inside the organization.

How can we actually improved them so, that's the last stage So in terms

of intervening in collaboration networks, how can we improve collaboration patterns?

Well there's some basic starting points, right?

The very first thing to ask is always is more collaboration actually needed?

Because it's very easy to say, look, those people aren't connected into the network.

They don't collaborate very much.

But that is not necessarily a bad thing.

More collaboration is not always better, because remember, the amounts of time that

you're spending talking to other people, asking them for information, asking them

for help or advice, or knowledge, or having them come to you and ask you for

help, advice, knowledge, those things are not always a good use of your time.

Sometimes they can really improve things, but not for everybody and

not all the time.

So the first question really is,

is more collaboration actually needed if we see a gap in a network.

Is it a gap we want to fill?

Then the next question becomes where is more collaboration needed okay?

So if there is a gap in the network or more likely there are multiple gaps in

the network, places where there aren't ties between people.

Do we actually need a tie in that particular place?

So thinking about how to build ties strategically,

not just trying to get everybody to collaborate more again, but

trying to figure out who are the most important people who need to be connected.

And very often they they're the people who are bridges between different

parts of the network, or could be bridges and perhaps aren't when they should be.

So often you'll see network structures that look pretty clustered.

Everybody in a particular unit talks to each other, everybody in another unit

talks to each other, but are there any connections between those units?

And that very often is a strategic opportunity where you need, or

could benefit from building more collaborative ties.

But identifying those opportunities carefully is going to be very important.

And then the third part becomes, well, how to increase collaboration.

Okay, we think we need more ties there, we need more bridging connections, but

how should we go about doing that?

And essentially there's two main ways.

And I'm just going to give some very top-line sense of this right now, but

obviously you can think about this in much more detail for

the particular situations that you might be faced with.

One is, you need to provide people with a motivation to build ties.

And very often for senior leaders in the organization that's going to be,

we really just need to call attention to,

we need to emphasize how important collaboration is for our organization.

And why it's important and emphasize that we want to promote it.

It could also be the case that you want to explicitly recognize and

reward collaboration.

And so firms that really care about this are increasingly building criteria

into their performance evaluation systems to say how much are you actually

helping your colleagues beyond the strict requirements of your own work?

And they'll use that as part of the performance evaluation system.

So actually rewarding collaboration if you really want people to do it,

it's going to be important.

And then, the other set of things is around providing opportunities

to build ties, right, because it's all very well turning people.

We want you to build those ties, but the more opportunities you can give people,

and usually that's in the form of exposure to each other, right, how can you give

people more exposure, more opportunities to get to know each other, and

to build those kind of trust, and build relationship.

And so it may be that you need some more meetings in-between different

processes and functions in the organization.

Maybe you can use conference calls, things where people can see

each other often are very important and maybe video conferencing.

Maybe you actually go all the way to have people rotate jobs,

spend some times in different parts or the organization, or

just to have them visit different sites if it's a geographically dispersed

organization, maybe organize events where people can come together.

So opportunities for

people to build those ties, in addition to the motivation to build them, are going to

be really valuable if you want to try to build more collaborative ties.

These are examples that are going to apply in many different situations.

But what I want to do for the remainder of the segment is to give you five more

specific examples of interventions in collaboration networks that

organizations have actually undertaken on the basis of network kinds of analysis.

Now the network analyses that they've used are often more sophisticated and use more,

different questions from the ones that we've been looking at,

which are simply kind of who goes to each other for information.

But, as a result, its the same basic methodology, and

I just want to give you a flavor and a feel for what these network tools and

techniques can enable you to do to improve collaboration inside organizations.

So I'm going to work through each of these five examples in turn.

And what you'll see is that in one case the implication was that we could reduce

employee overload.

The second was making global teams more resilient.

The third was reducing inefficiencies in collaboration.

Fourth is trying to get rid of silos or

reduce silos or big divisions between different parts of the organization.

And the last is trying to enhance career paths for people inside the organization.

So many different ways in which these tools and

techniques around organizational network analysis can turn out to be valuable for

improving aspects of collaboration.

So I want to work through each of these in turn.

Reducing employee overload, so

there's a lot of detail actually on all five of these slides coming up.

And I don't expect you to really go into great detail trying to understand

what exactly is in this chart and why.

Again, I just want you to get the basic idea and the feel for

what these kinds of methods can help us to do.

So this is a financial services organization.

It's real data from a network study in a financial organization.

And, what they were looking at here, is they asked people how

effective do you think everybody else in this sample is as a source of information.

So person one, two, three, four,

five report on how effective they are as a source of information, and

tell me whether you want more access to this particular person.

So those are the network questions that they asked In exactly the way that we were

talking about when we talked about how to map collaboration network.

And then they were able to plot how effective people were as a source of

information against a number of people who wanted to access those people more.

Again, don't need to worry too much about the details, but

what you see when you do this kind of analysis is that there are a small

number of people who add a lot of value in terms of collaboration in an organization.

And this is very common.

We often see numbers like this, around 5% of the people account for

up to 35% of the value-added collaborations.

So people basically in the top right hand corner of this chart

are really highly in demand, they are considered very effective and

lots of people want more of their time.

But the problem for those people, as they discovered in this financial

services organization, once it identified them through this analysis, they went and

talked to them and said, well, how's this going for you?

And what they found was that those people really felt very overloaded.

So they had a lot of people who were coming to them, and

who wanted more of their time, right?

And that's very problematic.

You have these super valuable people who are also feeling really overloaded.

You're really likely to lose these people to competitors

if you're not careful, right?

So what this analysis enabled these people,

this organization to do was to figure out well these are the very overloaded people,

but there's also some people revealed by this diagram who are considered effective

sources of information but who aren't utilizing nearly as much.

And so what they did was try to identify those well regarded employees who

are relatively under utilized and try to shift some of the burden to them and

say well can you take on some of the responsibility

of handling the kinds of questions, and the kind of approaches

that these very over-burdened people are getting all the time on their plates.

So, this was an opportunity to reduce employee overload by rebalancing

collaboration demands from the people who are really overloaded to people that

aren't quite as overloaded.

The second illustration is about improving the resiliency of global teams.

Okay.

And what they were doing here is through a network analysis,

they were able to identify which people were really peripheral and

who needed to be connected better.

So, again, this was a multinational agribusiness company.

So, a real large organization has global IT teams from around the world.

And, what they did was they mapped the networks

in exactly the same way we've been mapping them here

with between the team members in each of these global teams.

And, what they found, kind of like we saw for

our new product development team that had 15 people with Kevin out there

on the edge, is that there were some people who were very disconnected.

Right?

And so what this analysis enabled this

multinational company to do was try to identify who those people were,

and to really work hard to connect them into the organization.

And of course this is much more problematic,

because these are globally distributed teams, so

these people are probably in different countries.

So you've really got to figure out how to help them build ties that connect them

into the rest of the team.

This analysis again, allowed them to figure out who exactly needed to be

connected, and how they could be connected to make it most efficient.

Which connections would have the biggest positive impact on team connectivity.

And to ask people to take more responsibility to build those kinds of

ties, specifically.

So, the third illustration of an intervention that one organization took

was an interesting one.

It was about reducing collaboration inefficiencies, in this case,

through targeted coaching.

So, this was a major utility company.

And they realized that some of their people probably just weren't very

good at collaborating, although they were trying.

And so what they did they asked employees how much time they spent interacting

with each other, and how useful those interactions were.

And then again I don't expect you to really deal with the details of this plot,

but you can see these two axes plotted against each other.

So on the Y-axis, the vertical axis, the average number of times that an individual

was cited as a useful source of information and

on the X axis the average interaction times.

So what we see here is if a person is really you know considered to be very

useful, so up in the top bubble, and but

not taking too much time to interact with, that's pretty good.

But people who are really high on interaction time all the way on this

little lower bubble and sort of so so in terms of usefulness in interaction.

Those people are being much less effective, right?

People who you are trying to collaborate with, but

it takes you a lot of time to collaborate with them and it's not all that useful.

It's not really worth that time to collaborate with them.

You gotta do something about those people, because it's not really

having as much benefit, the collaboration is really kind of a wasted resource there.

And so what they were able to do, again, these were network questions,

that asked for every single individual, how useful is it to collaborate with them?

How much time does it take to collaborate with them?

So it's a network analysis that generated this kind of data plot.

And as a result they were able to identify the specific individuals that

needed coaching.

Right? And

to say well those people in that lower bubble, who are taking too much time and

arent' really valuable to interact with.

Let's develop personalized coaching plans for those people and

help them to collaborate, learn to collaborate more effectively.

So targeted coaching is an intervention that

was generated through this network analysis.

The fourth illustration here is about a company Money that

worked on trying to eliminate, or at least reduce organizational silos.

So those big, we often see organizations that have big divisions,

there's just very little communication between those divisions when they

operate as silos by building more across divisional ties.

So this is data from a Fortune 500 conglomerate.

And this is a conglomerate that had grown by acquisition.

So it was used to buying and integrating new divisions.

But the CEO and senior management where very concerned that the, top executives,

there are 126 of them.

Basically weren't really collaborating as much as they should across divisions, and

if you're growing acquisitions,

you kind of want synergies across your different divisions.

But some of them weren't talking to each other at all.

And so, they conducted a network analysis.

And here the network analysis was based on these 126 people

all across this large conglomerate.

And they asked how much do you collaborate with

people from these other divisions as well as from people inside your own division.

And here we see the raw data,

in some sense this is a very simple table that shows division one.

The bold numbers are how much people interact inside their division, and

then the unbold numbers or the lighter numbers are the numbers that show how much

the senior executives interact with upper divisions.

And what this company was able to do was say,

well where are those numbers really really low?

In other words, where are those divisions not

collaborating very much at all with each other, and is that a problem or is it

something we would expect to see given the nature of those particular divisions?

Again, it's not the case that if you don't see collaboration it's necessarily bad,

maybe those divisions just don't need to collaborate given what they do.

But they were able to identify a number of particular

divisional pairs that should have been collaborating more.

So identifying target's specific network connections that actually held strategic

relevance for the firm, and then try to intervene to build ties, encourage people,

give people opportunities to build ties across those divisions.

And also, in this particular company, they redid the network survey, and were able to

track changes in these ties over time to assess the impact of their interventions.

So another possibility, another way to use this network data, thinking about how to

build bridges, eliminate, organizational silos by building cross-divisional ties.

And the last illustration here is

one about enhancing career paths through better performance management processes.

So this is an illustration that comes from a global consulting firm.

And this was a company that mapped the networks of its partners,

it had about 80 partners.

And what it did when it mapped these networks

was that it discovered that a lot of departments were spending a lot of time

doing some things that were very valuable for the firm in terms of collaboration.

They were working with others to help them with their work.

But those things that they were doing, those collaborative activities,

were not recognized at all in the firm's performance management processes.

In other words, partners are being rewarded in terms of how much revenue

they brought into the firm, but they weren't being rewarded at all for

collaborating with other partners.

And in particular the network analysis found two main

ways that they were collaborating that were really valuable.

One was collaborating,

other words, helping the other partners in the firm to win clients.

Obviously very important for the firm, but it's not direct revenue production by me,

so I wasn't getting the credit for

it, but I'm helping other people do it, which is very important for the firm.

And helping other people, other partners to collaborate to serve clients.

So in otherwords, I'm sorry I'm going to so, let's start again.

So collaborating to win clients, but also collaborating to serve clients.

So in other words, you have a client and somebody comes to me for advice and says,

will you help me spend a little time on this project and

help me serve this client better.

And if I spend that time It's not direct revenue production.

I'm not being rewarded for it.

But of course helping that partner serve their client better is also very

valuable for the firm.

So once the firm realized through this network survey that

partners were spending time doing this valuable activity, valuable collaborative

activities around serving and winning clients, but they weren't being rewarded.

They realized that they had to change their performance management processes and

their performance evaluation systems to recognize the contributions of partners

who helped others to win new clients or to serve current clients.

So those are five very different illustrations

of different ways in which network analysis can be used.

And once you've done all the data collection and mapping and

analysis and evaluation, you've figured out what the problems are,

what can you then do to make improvements in your organization?

All the way from just building ties to changing performance management

processes targeted coaching and so on.

So in conclusion, we started off with this big question at the beginning of

this module how can we improve collaboration inside organizations.

And we worked our way through four main elements of this overall question.

We've thought about how can we describe collaboration patterns between employees,

how can we map these patterns, how can we evaluate them, and

how ultimately can we intervene to improve them?

And in order to do all this, we've used the tools and

techniques of organizational network analysis.

This is really a form of people analytics where we're using tools and techniques

that are very data-driven to try to improve the way that we manage employees,

and the way that employees work together to get the work of the organization done.

So when we think about using people analytics to understand,

evaluate collaboration inside organizations, we can use the tools of

organizational network analysis to go all the way through this process of being able

to describe what collaboration is actually happening inside the organization, being

able to map the collaboration networks between people inside the organization,

being able to evaluate and say, well, is that good or is that bad?

Do we like the way those people are collaborating?

Are they collaborating enough or not enough and

how it is affecting outcomes that we care about.

And finally,

if we think we need to make changes there are lots of possibilities for different

kinds of interventions that can improve collaboration inside the organization.

All the way from making it more efficient where it is happening

to building collaborative ties that are needed where it's not happening enough.

So I hope you found this helpful in starting to lay the groundwork for

understanding how to use people analytics to understand collaboration inside

organizations.

There's a lot more to go, this is just the introduction and the basics and

the foundations, but I think if you have all of this under your belt you're

going to know a lot have a very, very firm foundation for

building on as you go forward with trying to understand and

improve collaboration inside your organizations.

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