Understanding how social and collaborative technologies are being used by employees and other stakeholders is a top priority for many organisations.

This can sometimes be for defensive reasons – such as security and data leakage for example – but the overriding aim is normally to understand how the technology is supporting positive outcomes for the organisation.

The question is, how do you figure this out? More specifically, what data is needed and how can the data be accessed?

On-platform metrics

The simplest approach is to use the metrics provided by the platform itself. All leading enterprise software tools now provide access to data and reports, often through a dashboard or reporting module. These have certainly improved in recent years, and offer a quick, intuitive and often visual way of reporting on how your platform’s being used.

However the big drawback with focusing only on these metrics is that they typically only tell you what users have been doing on the platform. This might include individual-level metrics (such as number of posts, responses, follows and likes), group-level metrics, potentially conversation / topic analysis and increasingly, sentiment analysis.

While this provides a certain level of insight i.e. how people are using the platform, it doesn’t help you understand why it’s being used in these ways, and crucially what the tangible outcomes are of this activity.

The fact is that on-platform analytics tend to be narrowly-focused on the metrics of the tool itself, rather than looking at the broader picture of what’s driving these behaviours, and what outcomes are resulting from these activities. Coupled with this narrow focus is a tendency for on-platform metrics to ‘accentuate the positive’. After all, it’s far better to show a picture of active usage and ‘engagement’ on the platform than not!

Getting deeper insight

While these metrics provide some level of insight it’s an incomplete picture. The problem is, how do you improve on this?

There are two main challenges here:

1. Data and technology:

  • What does the platform provide itself in terms of data and reporting functionality?
  • What other data sets are required and available?
  • What tools and methodologies do you need to access and manipulate these additional data sets?

2. Purpose:

  • What questions are you trying to answer?
  • What’s important to your organisation or operating unit?
  • What will you do with this data and insight once you have it?

While questions regarding the data and technology are obviously crucial, I believe the starting point should be defining the purpose for your analytics activities.

Working back from outcomes

The key point here is that each organisation is different (sector, product/service, stage in business cycle etc) and therefore each organisation will be targeting different outcomes for its investment in enterprise social technology and supporting change initiatives.

Broadly speaking, the question is ‘what collaborative behaviours will support your strategic business outcomes, and how will our technology and behaviour change initiatives support these collaborative behaviours?’

To define your collaboration objectives you need to:

  1. Work back from your business outcomes and priorities (which are in turn affected by both internal and macro factors)
  2. Once you’ve defined your contextual collaboration objectives (for example, cost efficiencies through more efficient workflows or increased cross-selling by improved information sharing) you can then start to understand what behaviours will drive these outcomes (i.e. new ways of working supported by collaborative technology)
  3. This will in turn define which metrics you need to capture and analyse.

This ‘outcome-focused’ approach is absolutely the right way to define what it is you want to measure, and therefore what data you need to capture and manipulate.

Here are a few examples to show how this works:

Example #1 – Innovation through cross-functional collaboration

If your goal is to increase innovation then you first need a way to define and measure innovation for your organisation or business unit. You can then work back to the cross-functional activities and behaviours that drive this innovation, and specifically the way collaborative technologies are being used to facilitate these activities.

This provides your ‘brief’ for the data you require in terms of both innovation metrics and platform data (as well as what qualitative data you might explore to get a deeper understanding of the barriers and enablers of cross-functional collaboration).

Example #2 – Flattening the organisational hierarchy

One of the huge benefits of collaborative and social technology is its ability to connect different parts of the organisation, for example giving senior leadership insight to what’s happening on the front-line.

If that’s one of your goals, then standard on-platform metrics won’t do, as you need to map these to organisational data (which tells you where people ‘sit’ within the organisation), and ideally drill down further to understand not just how different parts of the organisation are connecting, but why they are working in this way and what outcomes are resulting from these interactions.

Example #3 – Improve employee engagement

The links between employee engagement and business performance are well documented, so a common objective for social collaborative initiatives is to improve engagement. But again this cannot be understood using platform metrics alone.

At the very least you need to correlate platform metrics with engagement survey data, and you may also want to dive down further to understand whether its platform usage driving engagement, or if it’s your (already) engaged employees who are most active on the platform (and indeed, whether the ‘direction’ matters).

What this means for you

These are just a few examples, but they highlight that to get more than superficial value from enterprise social analytics means taking a wider view of the overall behaviours and outcomes you’re looking to support with your collaborative technology and change initiatives. And it means you’ll need to augment your on-platform analytics capabilities with more powerful tools and methodologies if you’re to get the deep, actionable insights needed to truly unlock value from your investment.

Take a look at our case study explaining how a leading business information provider used enterprise social analytics to understand how their platform facilitated cross-functional collaboration and enhanced employee engagement. And to find out out more about Betterworking’s approach to enterprise social analytics, please get in touch.

Author: Chris Copland

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