OrgVue Blog

At the recent CIPD annual conference I presented a session on data led organisational performance. In creating this presentation it made me think hard about the steps we go through to get the most out of clients’ data. What struck me, was that although there is much progress in the HR analytics space, companies will always face data quality issues. Organisations merge, systems shift, processes change, and by our nature we are not as neat and tidy as we might wish! Data ends up in the wrong places, often duplicated, incorrect, or missing altogether.

So, how do you make having good quality data and insights an easy process? Below are 7 steps to get the most out of your people data, and my presentation from CIPD Annual Conference (05/11./14).

OrgVue Blog

Thank you to all those who joined our webinar on Data Driven Organisation Design with Rupert Morrison from OrgVue and Mark LaScola from On The Mark on 26th November 2014. Watch a recording of the webinar

Measuring the impact before, during and after design

Big data, analytics, and technology are the buzz words of today. However, despite the increase in access and size of data, too often design is shaped by inconsistent decision making based on gut feel, people politics and reactionary design. How can you use your data to optimise your organisation design?

Organisation design experts Rupert Morrison from OrgVue and Mark LaScola from On the Mark discuss:

• What data should you be using for organisation design?
• How do you create a baseline; collecting, integrating, and cleaning data?
• Where should you focus design efforts; analysing data and establishing targets?
• How do you create an overall design; processes, modelling, and scenarios?
• How can you communicate and implement your design effectively?
• How to track progress and change for sustained organisational performance?

Download a recording of the webinar

Download the webinar slides

OrgVue Blog

2014 saw real excitement and optimism spread through the HR function as the value from data and analytics began to be realised (see our blog, a breakthrough for HR analytics). But what’s in store for 2015?  We put together our top trends for HR analytics in 2015 for you to look out for and look forward to!

The rise of the HR analyst

Just a few years ago the terms HR and analyst may not have naturally seemed to fit. However, data and analytics is the new ‘sexy’ for HR. 2015 is our year for the HR analyst as the role grows into an integral part of HR and the business; gathering, analysing and feeding back insights to support business decisions.

Data Wrangling

As organisational change speeds up, the need to be on top of your data will be increasingly important. GET READY TO WRANGLE! Data Wrangling covers the steps of cleaning, converting and manipulating data into a usable, convenient format. 2015 will see new, intuitive connections between data and visualisations so you no longer need to handle data directly but can manipulate your data with ease through dragging and dropping visuals. Think Tom Cruise from Minority Report and you’re there!

Operational Analytics

Traditionally in HR, analytical reporting has been event driven. Transformation and change leads to a demand for reports snapshotting the organisation at one point in time. Operational analytics is one of the keys for HR in 2015. Organisational analytics will move towards a more operational process using technology such as apps, tasks and surveys to gamify the data collection process, allowing for ongoing, consistent reporting.

Social analytics

Social media has boomed in the last 5 years and it is the future, not just in our social lives, but our business lives as well. A big theme for 2015 will be to integrate social, sharable, and collaborative functionality into analytics to help organisations move away from static reporting and endless emailing back and forth. Imagine Pinterest but for analytics!

Cloud Integration

You may be sick of hearing about the cloud, but 2015 is where it will really take off. If 2014 saw organisations take their first steps towards moving to the cloud, 2015 will see a stampede. Integration is going to be a big buzzword in 2015 as organisations and HR look to connect multiple systems and information points from across the business for more comprehensive and in depth insights.

In conclusion, there is a lot for HR to continue to be excited about for 2015 surrounding HR analytics. Not only will HR analytics become more user friendly, interactive and fun to play with, but increasingly more value will be realised by HR and the business as technology progresses and HR professionals develop the skills to make the most of the analytical tools available. The emphasis is now on vendors to deliver usable, effective solutions, and HR to continue to embrace data and analytics to deliver lasting results.

In the coming weeks I will be blogging in depth about these trends and the impact they will have. In the meantime I would love to hear other trends in analytics you think HR needs to look out for in 2015. Please start the debate below!

To find out more about how OrgVue is revolutionising the way you see, plan and manage your organisation please visit www.orgvue.com

OrgVue Blog

We are to delighted announce that OrgVue 2.18 is now live and that from Monday 23rd February, all users will automatically be directed to the new version.

Over the last 4 months the OrgVue team have been busy implementing a range of usability enhancements, new features, and improving the speed of the application across the board. The new release sees OrgVue’s ability to handle large datasets greatly enhanced, with one client now using v2.18 to load 75,000 employees into the system. OrgVue 2.18  includes 6 new dashboards which I will summarise in this post. If you would like to download the full release notes, please follow the link at the bottom of the blog.

New Features in brief

• Ability to email PowerPoint and PDF outputs directly from within OrgVue
• Multiple hierarchies for visualising matrix reporting and associated operating structure
• Creating new datasets based on a template, preserving all the property definitions and baseline data
• Renaming datasets from the Home Screen
• Pause and Go buttons on Worksheet, Dashboard, Tree, Pivot and Chart controls
• Pause and Go button to suspend calculation of expressions globally

Enhanced Features

• Better startup performance, significantly reducing the time to load the home screen
• Performance gains enabling datasets exceeding 50,000 nodes and 100 properties
• Better performance in all date based dashboards
• More efficient Lookups from any Dataset
• Charting aggregated values side by side in Delta report to run scenario analysis
• Advanced search grammar (Find command)
• Zooming and highlighting interactions in Tree view to find people in an Org Chart quickly
• Revert changes to properties directly from within the filter control

New OrgVue dashboards; reducing the cost of being curious!

We know that running analysis can often result in more questions than answers which is why dashboards are now fully interactive. You can drag and drop any sub-section of analysis such as individual bars within a bar chart onto the Parking Lot to allow for focused and direct investigation so you can always find the answers you need. You can even drag that same data to the colour legend, filter control or other locations on the dashboard to modify data in place – making painting with data more universal than ever before.

Data Types and Patterns

People data is messy, incomplete and locked in multiple systems. So when you bring it all together, wouldn’t it be great if you could get an overview of your data quality? This is exactly what the data types and patterns dashboard does, showing you what data you have, where the gaps are and where your data is entered incorrectly.

Box Grid

The new box grid dashboard gives you immediate visibility across your organisational structure with quick and simple cross sectional analysis.

Waterfall

With the new waterfall dashboard, use your historical data to track headcount change over time and displays net change over a period of time. Perform joiner and leaver analysis by splitting by department, gender, recruitment channel, qualification level – whatever interests the business!

Calendar

Use the Calendar dashboard to aggregate and visualise date type data. For example, heat map when your peak recruitment times are by colouring by the count of employees started in each month.

Gantt

See the lengths between two time points across the organisation at a glance with the OrgVue Gantt Chart. The example below shows the start and leave dates of each employee, and the completion vs target dates of project objectives. The chart can be sorted and coloured by any dimension or measure, for example gender or RAG status.

Changes Report

It is not always easy to identify all the edits that have been made within a dataset or branch. The Changes Report provides a targeted report to summarise all the changes made into a single, simple to use view, aggregated by measure and grouped by dimension. A detailed change report for each node is also available, and these individual changes may be reverted directly from the report.

To find out more download a full copy of the release notes or contact us on info@orgvue.com.

OrgVue Blog

Last week I had the pleasure of chairing the CIPD HR analytics conference. There were some great speakers, including Angela Brandist from GreenThumb, Mark McGuire from Baxter Healthcare, Juan Mateos-Garcia from NESTA, Mark Lawrence from IBM and the University of Leeds and Tom Marsden from Saberr.

HR is on a voyage of discovery when it comes to analytics, and in the last two years it feels like real progress is being made. In my opening remarks I outlined my perspective of 5 general steps along the ‘HR analytics journey’:

Over the day, we heard many people emphasise the first three stages of this journey: starting with the intuition, building the hypothesis and then gathering the data to test it. Many organisations still have far to go, but several speakers encouraged starting small and ensuring above all that the analytics urge is based on a strong business interest in doing something with the end results. 

Out of all the takeaways from the event I thought I would share my favourite insights:

1. The agile approach: Craig Scriven from Warwickshire County Council and Peter Frampton from UBS talked about practical implementations, using an Agile approach to building analytical toolkits; building from user interfaces quickly, testing, then going back to the underlying systems to ensure projects keep moving forward and blockers are constantly removed.
2. Tackling data ownership: Who owns what data can be a contentious issue and a potential blocker. We heard about one case where ownership of data quality was transferred explicitly to business managers so they could correct data errors themselves and avoid the blame game with HR.
3. Finance and HR as friends: Finance and HR data have a lot of overlaps. Neal Barnes of Tullow set out the benefits of his approach towards workforce planning; integrating finance and HR data to understand fully and accurately the organisation’s headcount and where the workforce is across multiple countries.
4. Asking the question: HR professionals are becoming more inquisitive and bolder in their hypotheses. Michael Cowan brought an image of Lutheran transparency by pinning up publicly a list of 80 hypotheses that he wanted to test against the data. I wonder if we should all have such a list pinned up behind our desks!
5. Play in harmony: I particularly enjoyed Placid Jover of Unilever’s analogy of wanting his team to ‘play the piano’ – covering all the notes on the keyboard from descriptive reporting, through analytical insight all the way to prediction and intervention.

However, despite many stories of insights from organisational data, it is clear that many still remain to be explored. In the morning session, a straw poll of the audience suggested that 75% had a view of the number of vacancies in their organisation or area, and perhaps 65% had a view of the average time to hire, only 5% or so said they had a view of their quality of hires. An exciting challenge to connect the dots – perhaps one to be reported on next year.

This is the challenge now for HR, to join the dots. And it isn’t too difficult. This data is already in the hands of HR professionals –the fascinating area of what I call ‘middle data.’ This exists between input data, such as staff demographics, pay and training and output data such as performance, absence and turnover. The ‘middle data’ informs about the journey from one to another. For example, the impact self-directed learning, teaching and communications systems.

It is this data and the connecting of that data within and across the organisation which I hope HR professionals will start to bring to life. This is how we will start being able to  see correlations between those who contribute to learning, those who use communications systems and those areas that show differences in performance. An exciting area to investigate for return on investment.

I look forward to hearing everyone’s analytics story develop and be put into practice at future CIPD learning events.

OrgVue Blog

Many business transformations are undertaken to align an organisation with its strategic goals. The desired end result? To ensure the customer value proposition, profitability and target operating model all work smoothly together.

Traditionally, transformation has been regarded as large-scale restructuring of an organisation, reacting to and playing catch-up with internal and external changes. Many organisations are utterly exhausted as they stumble from one transformation to the next without ever realising the value of their previous transformation programmes.

Using workforce analytics in the areas of Organisation Design, Workforce Planning and Transformation Management can help maximise the value of business transformation and minimise the disruption.

Want to find out more?

On Thursday 23^rd April at 11.55am, Julian Holmes, Director at OrgVue, is running an Organisational Transformation  workshop at the Tucana People Analytics Conference 2015. The workshop will explore 3 key questions:

• What is critical for organisation design? How to focus on the critical parts of the organisation that will deliver the greatest business benefits through cost reduction, customer value proposition or new business capability via enhanced organisation design
• How can you connect supply and demand for workforce planning?  How to understand links between the business and workforce over time through enhanced workforce planning
• How can you control the implementation of transformation? How to understand, manage and minimise the impact of transformation effectively through enhanced transition management

Julian will demonstrate how using new tools and methods with Workforce Analytics can accelerate and support your transformation programme.

What do you think? Leave your comments below.

Find out more about the conference

OrgVue Blog

Today I was at the second day of Tucana’s People Analytics conference and attended a great session from Peter Howes. Howes is one of the original founders of InfoHRM, which was bought by Success Factors and then SAP. It was fascinating to hear his 5 most important analytics recommendations:

1. Segment – don’t use aggregated data. Sales people data is very different by high performers vs low performers. Segment by personal characteristics and segment by role characteristics.

2. Integrate people data with business data, such as revenues, expenses and CSAT.

3. Integrate people data from multiple sources, such as engagement, absence and training.

4. Data quality is key – but you can’t wait for it to be perfect. You get data clean by using it.

5. Tell the story – to have an impact, you have to communicate the story in business terms.

The danger of aggregated data is worth repeating: Howes described these as ‘generally dangerous’. He explained that it is vital to drill down: “We did a study of 18 of our clients in Australia. We looked at 7 benchmarks – including voluntary turnover by organisation unit. We excluded the 1st and 10th decile. And the range was 0% – 35% while the average was 16%. But the turnover rates in one company were much higher for their high performers in critical roles. It was meaningless to compare that company’s total turnover with the average of other companies’ total turnover.”

Interestingly, Howes suggested that Success Factors is now exploring detailed transactional benchmarks, such as high performing professionals in their 3rd year of position tenure, as a way of overcoming the aggregation issue.

Being sensitive to segments, and valuing basic steps in analytics aligns to something Max Blumberg said on Day 1 of the conference: while people describe the classic analytics journey from description, through correlation, to prediction, many organisations spend most of their time and get most of their value from the first stages.

As Howes commented, the majority of this work is applying basic maths (‘Grade 4 maths – addition, subtraction, division and multiplication’) and getting good simple descriptions of the organisation. A rough guess of activity mix and value achieved from Max & Peter’s discussion… does this look like the organisation effort in your business? 50% – Description 30% – Correlation 5% 15% – Prescription

This was Howes’ top quote from the session: “I’d like every HR practitioner to spend 5-10% of their time doing HR analytics.”

Want to find out more? Come visit the OrgVue stand at the Tucana People Analytics conference.

Photographs courtesy of Andreas Grieger.

OrgVue Blog

‘Playing the Piano’: from Description via Correlation to Prediction

Last night, Giles Slinger, Director of OrgVue Product, gave a talk for the CIPD North London branch on HR Analytics. The topic was a whistlestop version of the HR analytics training given at Concentra (the last two free sessions are available here).

 Forget prediction! How to get value from your HR Analytics…

·       Why the data will always be messy

·       Why visualisation is key

·       Why HR and Finance should be best friends about data

·       How analytics leads to intervention

·       The importance of story-telling

·       Give-away: a free set of HR re-design cards

His presentation can be downloaded from here: Orgvue HR analytics.

For those wanting to try OrgVue, One Hour with OrgVue instructions are available here.

Any attendee who would like to obtain the HR Function redesign cards or instructions, please contact: giles.slinger@concentra.co.uk

OrgVue Blog

At the second day of the Tucana People Analytics conference, I attended a fascinating talk by Julia Howes of Mercer on Strategic Workforce Planning.

According to Julia, huge changes are about to hit the economy in the next five to ten years, including the automation of many roles. At the same time, people are feeling more and more disengaged from their work.

Demographic trends are also impacting the economy: with an ageing workforce and population requiring more services, Julia believes that, in the near future, more and more workers – especially women – will start working as carers.

In the face of such changes, Julia offered six valuable pieces of advice for building a stronger workforce using Strategic Workforce Planning:

1. Have a clear but flexible methodology
2. The business must own the forecast and plan
3. Focus on your critical workforce segments
4. Plan for more than one outcome
5. Your workforce plan should tell a story
6. Workforce planning is not an event: convert from a one-off project to a regular embedded process

For successful Strategic Workforce Planning, Julia explained that ‘telling the story’ overrides most other considerations since without a story, no change will ever occur. Julia gave a great example of this: visualising the future demand for 4 different roles in a business, she showed a slide without any axes or numbers on the level of demand (the photo didn’t turn out too well, but hopefully you can see the general trends).

Her point was that workforce analytics can provide a sense of direction so that action can be taken, but precise numerical values are not always necessary. In fact, they can distract from the overall message. Julia explained that, when it comes to HR data, people are often afraid of using it if it’s not 100% accurate. Since it is practically impossible to have 100% accurate data, she advised that data doesn’t have to be complete to be good enough to give a sense of direction: as she said, “it’s not about 8 FTE or 9 FTE, it’s about taking the direction”.

So how do businesses ‘take the direction’? Julia outlined four key steps for simple Strategic Workforce Planning:

1.  Strategic insight

Organisation imperatives and Talent imperatives generate the Demand Scenarios for key workforce segments. Identify the roles that are critical to the business strategy over the next 5 years and focus on these.

2. Measure the gap

By extrapolating current trends, estimate Talent Demand and Talent Supply, calculate the gap and identify risks.

3. Model talent management options, including:

• Buy: purchase external talent through increased recruitment and future candidate engagement
• Build: develop talent from within the organisation through increased training and development activities
• Borrow: borrow or rent talent through contracting with agencies or consulting firms
• Bind: retain existing talent through improvements in the employee value proposition
• Transform: use technology, a different way to organise work, and training or motivation to increase labour productivity
• Regroup: change the business strategy due to unavailable labour resources or prohibitive costs to implement

4. Take action by implementing the options above:
Attraction, Retention, Engagement, Career Development, Performance, Rewards, Leadership and Mobility.

I would then add a fifth crucial step to this process which is track. This is not simply a case of tracking headcount. Your headcount is simply your input into your workforce. The key is to connect this to business outputs and KPIs whether that be performance, sales scores or customer satisfaction. If you track, the first 4 steps become iterative, allowing you to hone your workforce over time and ensure plans evolve alongside your workforce.

For more on our approach to workforce planning read our blog on 3 simple steps to workforce planning

OrgVue Blog

Example of impact tracking: chart showing roll up of process costs

Sometimes it can feel as if we spend all of our time working ridiculously hard on inputs. We rarely take the time to assess the outputs and results of our work.

Organisations often bounce from one set of initiatives to another. An initial transformation project gets overtaken by an event such as an acquisition, or an adjustment of business priorities. Things rarely get finished. Or rather, it can be very difficult to finish something and feel like it is finished. Because in reality, when it comes to organisations, a project can never be ‘complete’. There is always the next phase of challenges to overcome and improvements to be gained. Rarely do we ever get the chance to look back on the work we’ve done and feel satisfied that we did a “good job” and, even more importantly, that we can prove it to the business. I think this is one of the reasons it is so difficult for those dealing with organisational and people effectiveness to put forward a powerful business case.

But no longer. It’s time for us to put the outputs first. HR is moving from an operational to a strategic force in the organisation and with this, it’s all about impact. Three recommendations that I’ve found useful in my work:

-          Connect the project to the business: before any project starts what are the key aims and how do they relate to the business?

-          Select your outcome metrics: Make sure the benefits you are planning to realise can be tracked in a way that actually means something to the business. For example:

• Sales performance
• Attrition rates and recruitment costs
• Productivity rates

-          Track the results: Once you have set up your measurements, keep tracking them. Not only does this mean you can celebrate and make a killer business case when things go right, but if things go wrong you can tweak and refine the project to have more impact.

So what does this actually look like in practice?

Over the next few weeks I’ll be exploring some key case studies of businesses that measure the impact of their HR inputs and show results in numbers. These examples will show how HR can prove its value at the boardroom table.

If you have a great story, please share it with me: Giles.Slinger@orgvue.com. I’d be happy to write it up and share it as part of this series on HR impact.

OrgVue Blog

It’s easy to see results from Sales and Finance data. But in the HR function, where it’s practically impossible to assign people a single number, it can be hard to measure outcomes.

For this series of blogs about the impact of HR, I’ll be sharing some key case studies of businesses that measure the value of their HR inputs and show results in numbers. First up is consumer electronics retailer Elkjøp and its recruitment advisor, a recruitment analytics firm called cut-e.

Elkjøp is the largest electronics retailer in the Nordic countries with 400 stores across 6 countries and 9,500 employees. At the time of the intervention their company was suffering from 20% annual staff turnover, including some recruits who only stayed for very short periods at the company. Recruitment processes were taking too long, making them expensive and inefficient. The company was paying significant amounts to headhunters for external candidates for management positions. Finally, choosing to hire people who turned out to be unsuitable for sales roles was costing the company potential revenue.

At the start of the intervention Elkjøp chose four areas to improve recruitment, measured through cutting costs and increasing sales:

1. Failed hires: new recruits who left in their first 6 months, and the losses involved. Elkjøp calculated that 200 failed recruitments annually cost it €4.6 million per year. By reducing this by 80%, they aimed to save €3.68m euros.
2. Internal resources: Elkjøp identified recruitment process improvements that could take 3 hours off each hire, saving 6000 hours per year, at a value of €241,800.
3. Internal recruitment: by recruiting managers internally as opposed to via an external supplier, Elkjøp would save €864,150 euros.
4. Psychometric tests: Elkjøp used psychological tests to select the right people for the right position. Elsewhere, cut-e had shown potential to increase sales by 14% by choosing suitable candidates. If similar results could be achieved by Elkjøp, this would translate into €29m in extra revenue. Together Elkjøp and cut-e designed an assessment including ability tests, personality tests and interviews to find the best candidates. They prepared bespoke reports on progress for regular updates, then fine-tuned the process continuously using feedback from applicants and store managers.

Here are some examples of the tests they used:

By addressing these four areas, the recruitment team was able to cut costs, save time and increase sales revenue. Here’s how the company expects to benefit:

• €3,680,000 was saved by reducing failed hires by 80%
• €241,800 of time was saved by saving 3 hours in administration per hire
• €164,215 in external costs was saved by recruiting 30 management positions per year internally
• €5,800,000 in extra sales/margin from having the right personality types in sales roles

The total upside was €9.8m euros – which is being documented in follow up studies over the summer of 2015.

This graph shows Elkjøp’s largest source of gain: the extra revenue from right personality types for sales.

The intervention was hailed as a massive success. Store manager Elgiganten Täby said: “The person who came up with using cut-e is a genius and deserves a medal!”

By looking at impact, not only did Elkjøp drive 10 million euros of benefit to the bottom line but they showed the value of HR. Elkjøp’s HR team was highly disciplined in setting out the case for change, intervening in a flexible and evolving way and tracking the impact afterwards.

If HR ever wants its strategic seat at the board table then this is how; by doing something well and making sure the business recognises it has done something well. This means showing the business the results in numbers. I am excited to see more and more of these case studies emerge as increasing HR functions start demonstrating the power of their role and the power of people within the organisation.

Look out for my next post  in the HR impact series. If you have a great story about how HR has changed your business, please share it with me: Giles.Slinger@orgvue.com. I’d be happy to write it up and share it here.

OrgVue Blog

Three months after the release of 2.18, we are delighted to announce the arrival of 2.20. These release notes will give you a summary of the new release and how to make the most of the new features.

• Pivot View: depending on the number of nodes in a single cell,  individual nodes within the pivot view may be displayed as cards, or as a summary graphics. For cards you can select different card styles and sort their values. For summary cells you can select different shapes including circles, pictographs, sunflowers and treemaps (clockwise in the image below).

OrgVue 2.20 pivot view analysis: Tenure vs Grade, coloured by performance

• Search: a search box has been added to the right side panel. Simply type the text to find and search through all text fields to find matches, grouping the results by the property in which the match was found. More specific searches can be performed by adopting the find syntax (but dropping the “find “ prefix). Use the pipe character (|) for or queries.
• Colour control: a new standard set of colour palettes have been provided to make it easier to spot trends and interrelationships. Colour gradients may be calculated using linear interpolation of RGB, or by using an LCH based colour space. The latter may provide more vivid colours within the gradient, but will not work with all colour combinations.
• Paging control: usability and performance enhancements have been made to the paging control including a select box so you can jump to any page. You may also switch pages using Page Up and Page Down via the keyboard. When paging through nested pages, empty pages are now skipped automatically.
• Filter control: summaries within the filter control are now shown to 6 significant figures, enabling the filter control to be used more easily for rapidly answering basic statistics about your data.
• Ghost nodes: when visualising an organisation chart where a filter has been applied, the details of the ghost nodes (those required to draw the hierarchy, but which otherwise lie outside the filter), will now be displayed without colour in the Summary Card. Further unselecting the Ghosts checkbox in the Properties pane will reduce the Ghost card to display just the Title and Subtitle.
• Removal of Home icon: the home icon, previously shown at the left of the toolbar, has been removed as many users reported issues clicking on this icon in error when navigating between tabs. In order to return to the home screen, the close icon on the far of the toolbar should be used instead.

If you would like more information about the OrgVue 2.20 release please visit the OrgVue forum for a full set of release notes. If you are having any troubles with the new release please get in touch with support@orgvue.com

OrgVue Blog

When working with any data or information, there is a constant battle to locate it, collect it and keep it up to date. Three of the most rapidly developing features of OrgVue are the interfaces: webforms, surveys and task forms. Each of these “sit over the top” of the main OrgVue Workspace, acting as a simple, user-friendly layer that allows users to interact with their data.

Because they are more streamlined than Workspace and present only a limited amount of data, interfaces are a great way of increasing involvement from people across the business, even if they aren’t comfortable with new technology or haven’t received OrgVue training. They can also be viewed on mobile devices.

Webforms

Webforms are online forms that can be generated from any OrgVue dataset with the click of a button. They provide a simple and streamlined interface for updating specified information. This is extremely useful to crowdsource information from across the business on an ad hoc basis as people can provide information without engaging directly with the OrgVue workspace.

A colleague of mine recently conducted performance appraisals using webforms designed around the client’s process. They sent them to all the organisation’s managers and employees before aggregating the results. Using webforms made this process successful because they are:

• Configurable: Choose what fields will appear on the screen and how to display them
• Versatile: Make use of a range of input types, including calendars, dropdowns and number sliders
• Secure: Use email addresses to restrict access to only the nodes they have permission to see
• Multi-purpose: Generate several webforms from a single dataset by tagging properties
• User-friendly: Employ rich text formatting and HTML to customise the standard template

Surveys

Surveys are similar to webforms in that they act as an additional layer on top of the Workspace and allow easy input of information. However, surveys contain a number of features that webforms do not:

• They don’t require respondents to have an OrgVue account
• They have convenient add-ons like email circulation and header/footer/thank-you messages
• They allow admins to send out invites en masse and track responses

These features make them ideally suited to gathering data from large numbers of respondents. A few months ago, I used an OrgVue survey to register expressions of interest from employees in an organisation undergoing transformation. It took a couple of minutes to send out personalised emails to 700 employees in batches so the transformation team and I could address different language regions.

Adding messages to the start and end and customising the formatting to the client helped gain buy-in from employees. In addition a key benefit was that we were able to track the progress of surveys from being “Sent” to “In Progress” (when an individual had edited and saved their answers) to “Complete” (they had submitted the survey). Once all respondents had completed the survey, it was easy to use a lookup to pull their responses into the current employee state dataset to inform the next phase of the project.

Task forms

Task forms are the newest interface that has been developed for OrgVue. Unlike webforms and surveys, tasks are custom-designed by Concentra to fit the particular needs of a client, and all the tasks within a particular tenant can be accessed via a single URL.

Tasks help users to input data following a pre-defined process. Each task guides the user through a series of input screens and writes the information they enter into OrgVue. There are 3 main features that make tasks ideally suited to managing processes:

• They are dynamic, meaning that the information you enter effects the screens you see
• They allow for workflows, meaning managers can review and approve data entered
• They are able to extract and write data from/to multiple different OrgVue datasets, allowing them to be used to manage complex processes fed from different sources of information

Individual users cannot configure the structure of task forms themselves but there are some configuration options available – e.g. defining dropdown lists and default options from datasets in OrgVue Workspace.

Tasks are also a rapidly evolving area of the product. In the last 12 months, we have developed tasks for: objectives management, building your organisation hierarchy, conducting 360 reviews, managing employee recruitment, consultation and retrenchment, and validating changes to the structure of departments. Alongside each of these releases have been an array of new formatting and features, including using tasks to send emails and print PDFs.

The various OrgVue Interfaces are fairly new – task forms have only existed for 18 months – and yet they are being used in a variety of use cases, from succession planning to OD. The near future will see even greater use – with a complete update of the webform UI, increasingly flexible formatting options for surveys, and continuing advancement of task form functionality. Watch this space!

OrgVue Blog

OrgVue is a tool designed to manage organisational data. Organisational datasets are often incomplete and stored in multiple places. Before you can do any integration or cleaning of these data, you need to get the information into OrgVue in the first place. These are the main ways of getting data into OrgVue:

-        Directly entering data into datasets

-        Copying in from Excel

-        Auto uploading from a database

-        Using one of three kinds of interface:

1. Webforms, which allow multiple users to update various aspects of a dataset without logging in to Workspace.

2. Surveys, which gather one-off information from a large number of respondents and aggregate the results.

3. Task forms, which guide users through a data entry process, especially if it involves dynamic workflow / approval.

(For more information on webforms, surveys and task forms, check out my post on OrgVue interfaces: how to use webforms, surveys and tasks.)

Image 1: different ways to get data into OrgVue.

How do I follow these processes?

Entering data directly into OrgVue is as simple as clicking “add node” and typing into cells like you would in Excel. The most common way of getting data into OrgVue is pasting it in from another source, usually Excel, but also Notepad, MS Word, or even a table in an email. All you need to do is select the data you want to copy, including headers and avoiding empty columns, and hit Ctrl-C.

The advantage of this method is that it also lets you define a hierarchy – as long as the source data contains a unique ID field and a parent ID, and something that you are happy to use as a label, OrgVue lets you instantly assemble org charts. OrgVue also lets you merge several worksheets into a single dataset. Paste merging works like a repeated VLOOKUP in Excel (or a left outer join in SQL, Tableau, or Alteryx), in that you need to have a property common to both tables and this is the field used to merge data into OrgVue.

There are times when manual integration of data, even via a webform or paste merge, is not ideal. When pulling data from a variety of databases, manual intervention and creation of Excel spreadsheets becomes time consuming and leaves you prone to errors.

OrgVue provides an auto-upload tool. Saving your source data in a nominated folder, you can schedule regular loads into OrgVue, and carry out more sophisticated actions like:

-        Automating scheduled uploads from a Windows Server to OrgVue

-        Merging multiple CSVs into a single dataset

-        Uploading behind a proxy

-        Artificially constructing a dataset that contains a history of past values

How else can I connect the data I’ve imported?

Once your data is in OrgVue, there are a number of different ways of combining, connecting and relating it to produce the insight you need. Broadly speaking there are 4 types of action you may come across:

-        Lookup: connection between a primary dataset and a secondary lookup based on a unique field common to both datasets. Used to store values in a single place and reference them multiple times (the ID matching is the same as in a paste merge, but the datasets are kept separate)

-        Link: many to many mapping between nodes in 2 different datasets (like a Lookup it can be used to pull read-only values from one dataset into the other, but it allows for many-to-many relationships between nodes in each dataset)

-        Pin: saving a view of the dataset as it is currently configured (colour, filter, chart etc.) where the data stays automatically up to date because it is just a version of the main dataset. This is perfect for building charts and dashboards and sharing them with colleagues

-        Branch: saved copy of a dataset that can be edited separately but can be updated from the “trunk” (baseline) dataset and request changes to be pushed back into it. Analyse the difference between Trunk and Branch datasets using delta analyses – ideal for cleaning data on a large scale or doing scenario modelling during an org re-design.

OrgVue Blog

In supporting clients with OrgVue I get asked about a range of issues, from tenant admin (someone’s forgotten their password), through troubleshooting defects (that usually aren’t defects) and supporting some of the more advanced features (e.g. lookups, security), up to consulting advice (“how could I write this expression more efficiently”).

The vast majority of support time is spent answering questions that are in the training materials or online forum.   So I thought I’d put together a blog mini-series outlining 3 processes to help solve issues when they come up in OrgVue.

Abstract the problem

It is easy to panic when you can’t see what you expected. Instead, ask yourself: “what was I expecting to see?”, “what am I actually seeing?”, “what aspect of OrgVue’s behaviour might explain this expectation gap?”

For example, one of the most common questions I get is: “why can’t I see the whole hierarchy?” I get this question once every couple of weeks, and almost without fail the answer has been one of the following:

1. the user has an applied filter

2. the “expand to level” selection is not what the user expected

3. they have accidentally changed the “Parent By” to something incorrect

4. there is pagination applied to the dataset

5. the tree type is not intuitive – e.g. columns

Check these possibilities using the icons highlighted in the screenshot below:

This a useful checklist if you find yourself looking at an org chart with a hierarchy you weren’t expecting. But to boil it down to the bare essence, ask the question, “what might be happening in OrgVue to make my hierarchy look wrong?” The answer is either (a) you’re not seeing the whole hierarchy (filter, expand to level, pages), or (b) the hierarchy you were expecting isn’t being generated (parent by), or (c) the hierarchy is present and correct but not being drawn intuitively (tree type).

If you have problems using OrgVue, send me an email: Ben.Marshall@orgvue.com

OrgVue Blog

Each piece of software takes getting used to, but even after years of exposure, people make mistakes. No matter the technology, the ‘bioware’ is often an issue. Whether it’s responding to client questions or troubleshooting for myself on the fly, if I’m faced with an unexpected outcome and can’t think of anything after abstracting the problem, the next thing I check is whether there’s a simple inconsistency that’s been missed. I tend to run through 6 checks of the OrgVue set up and my access to it. More often than not, I get to an answer before I finish the list:

1. Am I on the right web address? (correct environment of demo vs live, most up to date version number[1])
2. Are my credentials correct?  (am I logged in using the correct information, is my account correctly set up in the users dataset)
3. Do I have the appropriate permissions? (appropriate role type, dataset tagged for access or lookup, properties secured correctly, any typos in an “owner” property)
4. Am I looking at the most up-to-date information?  (does the issue persist if I recalculate the dataset, reload the dataset or tenant, refresh the browser)
5. How well is my browser performing? (IE can be slow, sometimes Chrome doesn’t copy to clipboard, Firefox can block Flash player)
6. Are there any likely technical interferences? (is Flash installed and up-to-date, are there any Firewalls that might be blocking traffic, NB. battery saving mode can slow down running)

If none of these are the root of the problem, and after following the next step you’ve still not found the solution, you may need to get in touch with the support desk. If you do so, it is incredibly helpful if you also provide the information listed in these 6 checks. It will help Support rule out issues and replicate your conditions when testing the problem.

OrgVue Blog

In my last two blog posts about problem solving in OrgVue, I looked at abstracting the problem and six simple checks to help resolve any issues. But sometimes you still can’t work out what’s causing the issue, even after you’ve broken the problem down, and tested all the simple possibilities. In these cases, people often find the most efficient way of getting hold of information is to try the training materials (manual, online videos, forum), then ask an advanced user/superuser, then contact support@orgvue.com if they’re still having trouble.

At this stage, troubleshooting closely resembles the scientific method. First we try to take the observed behaviour and split it into all its component parts. Then we come up with a hypothesis about where the problem might be originating, and test it by making a change, keeping everything else the same and seeing what happens. You might iterate through several theories but as long as you capture all the factors that affect a feature, the potential reasons why each might not be working, and disprove, you’ll discover the reason for failure.

I recently had an issue with an expression not working correctly. After going through the above stages I started to ask questions like:

-        “If it doesn’t work in properties; does it work in the Expressions manager?”

-        “Can it be broken up into smaller expressions that work individually?”

-        “Does it reference any other values or expressions that might be invalid?”

-        “Are there any advanced features involved e.g. settemporary, or lookups, that make it look like the problem is with the expression when it’s actually with another feature?”

The more precise you can be when defining the problem, and methodical when testing it, the easier it will be to rule out its possible causes. This also applies when describing issues you can’t solve to the support desk. For example, descriptions like “my data’s been corrupted” or “the screen’s frozen” could be written more specifically as “the cells in my lookup properties are displaying expressions rather than meaningful values” or “I can’t see the text under the donut icons in tree view”.

I hope some of these checks and methods help! If you ever have questions or ideas, the OrgVue forum is a great way for OrgVue users to find technical answers, share best practice and suggest improvements to the product.

Otherwise you can get in touch with me: Ben.Marshall@orgvue.com

OrgVue Blog

Like all software tools, OrgVue is built to perform quickly, and each release includes features to decrease calculation time, make lookups more efficient, or increase the number of records that can be handled. However, users also have a lot of influence on how well their dataset or tenant is performing. If you experience slow evaluation times and Flash crashing, try these 5 pointers:

1.       Write expressions in the property value box (not individual cells)

Expressions are the biggest contributor to a slow dataset, and you can mitigate this by optimising where you write expressions, how you write expressions, and how you configure them. If you want to create a calculated property, writing the expression in the property value box (in the Edit Property dialog) is by far the best way of doing it. Writing directly into cells means that the expression has to be compiled for every node, rather than just once, and can cause larger datasets to run very slowly.

 2.       Write expressions as efficiently as possible

OrgVue expressions are written using Gizmo, a JavaScript-like language. Whilst you can’t be expected to write expressions like a developer, there are some simple rules you can follow to make your expressions quicker to run and proof check:

1. Don’t repeat yourself
2. Make expressions easy to follow
3. Try to keep up-to-date on the newest syntax
4. Bear in mind what the purpose of the expression is.

For more explanation of these, see part 2 of this blog series.

3.       Configure expressions so they only re-calculate as needed

As OrgVue’s default, every time the data are loaded it scans all the cells in a property until it encounters an expression. This increases the time it takes OrgVue to load or re-process a dataset. However, you can use the 5 evaluation options in the Edit Property dialog to dramatically increase performance by stopping expressions needlessly recalculating.

Avoid using the ‘auto’ setting which detects expressions (at a high performance cost) and evaluates them whenever data changes. Choose the ‘none’ setting when no cell for this property should be evaluated as an expression. Choose the ‘node’ setting when the expression only needs to be re-evaluated when the node is changed. Choose the ‘hierarchy’ setting when the expression is dependent upon the node’s descendants e.g. as node.rollup(“salary”,”sum”).

If you only need the expression to be calculated once (or rarely) and remain static most of the time, add a “!!” to the end of the expression. The results will now be hard-written into the cells (like if you had chosen “Initial” value mode). To trigger a recalculation, remove all the values from your property by blank splashing (!!*).

4.       Use ‘settemporary’ (and ‘script’ mode) to evaluate all your properties in one

Rather than typing individual expressions directly into the Default Value box for properties to be calculated, OrgVue enables multiple properties to be set via a single expression held either in a specified property or executed via a script. This means only one expression is evaluated for each node but a range of calculated values are returned for multiple properties; this increases performance in datasets where multiple properties contain calculated values and allows the reuse of traversals (expressions calculating up and down the tree).

To use settemporary:

1. Create  a property called “Expressions” (or indeed, any other convenient name),
2. Set the default value of this property as “node.settemporary({ a:x, b:y, …,      c:z})” where:

a, b, c = the names of properties that are going to be populated with calculated values, and

x, y, z = the expressions to be evaluated

NB. The names that need to be listed are the property key values, exactly as they appear in the Edit Property dialogue. You cannot include any dependencies in the settemporary expression, so you couldn’t include bonus (10% of salary) and total cost (salary+bonus).

3. Set the evaluation type of all the properties evaluated in this way to “script”.

5.       Keep your tenant tidy

How quickly your tenant opens and performs depends on 3 main factors:

• The number of datasets (inc. links and reports) it contains
• The size of those datasets
• The amount and complexity of calculations across the tenant

To make your tenant run as fast as possible, you should consider:

1. Deleting old (versions of) datasets
2. Only creating links between datasets that are being consistently used
3. Combining lookup datasets so they do not overlap (ie. no 2 lookups share the same unique id)
4. Storing any scripts (e.g. for custom dashboards, colour palettes, or containing lots of expressions) centrally. For more information on how to do this, get in touch with your superuser or an OrgVue consultant.

Hopefully these methods will help you to use OrgVue as efficiently as possible. If you ever have questions or ideas, the OrgVue Portal is a great way for OrgVue users to find technical answers, share best practice and suggest improvements to the product. I’ve also written a series of blog posts about problem solving in OrgVue: Abstracting the problem, Six simple checks and Not seeing what you expected?

Otherwise you can get in touch with me: Ben.Marshall@orgvue.com

OrgVue Blog

The CIPD HR Analytics conference in October 2015 had high quality presentations which showed in every case how to connect HR analytics to business impact. It’s a credit to the profession, which is starting to draw real business value from analytics.

Can we do analytics? A change in mood

In the 5 conferences in which I have been involved since 2012, there has been a marked shift in the mood of the HR profession:

• Gloom: our data is simply not good enough, and it’ll be a 5-8 year journey to fix it
• Hope: there appear to be ways forward, we are setting out on the journey
• Excitement: there are tools and methods we can apply
• Insights: we are getting analytical findings that are important to the business
• Intervention: we are making HR or business changes and affecting business outcomes

Who are the HR data leaders and analysts?

Those getting the most from their HR data often come from outside the HR function, and many of our speakers had started their careers in the business, in Finance or IT.

How many analysts do businesses have? HR Analytics is an unusual occupation – usually small teams even within very large businesses. A few of the speakers shared their numbers, and looking at a range of businesses from 9,000 to 94,000 people, the analytical headcount ranged between 1 and 5 HR Analysts per 10,000 employees. (The HR headcount as a percentage of employees was: 1% – 2.7%).

6 key takeaways:

1. Dirty Data vs. Clean data: Don’t worry! Often you’ll find it’s clean enough. As one of the speakers said “If
   it’s 11 or 12 doesn’t matter; what matters is, is it going up or down?”
2. Numbers vs. Visuals: “One picture beats a thousand line spreadsheet every time”.
3. One dataset vs. multiple datasets: Better together. Combining HR data with business data (on customer outcomes, real estate costs, procurement spend, sales) multiplies the value of insights.
4. Internal vs. External data: the Permeable Organisation. Two companies talked about integrating publicly available LinkedIn profiles into their HR systems. One was trialling using Facebook data to identify existing employees who could recommend (or not) target recruitment candidates and then give them a pre-drafted email to reach out to a recommended contact.
5. Single dimensions vs. Linked dimensions: getting insights ‘At Right Angles’ to the original data, such as linking processes to people let one company ‘truly understand the value of customer support’.
6. Analysis vs. Action: pretty much every speaker argued that analysis had to be converted to action with measurable impact:
   • A media company has “Insight Champions” to convert insights to results, for example, and has halved absence by identifying and acting on hotspots
   • A food company changed their Induction method to engage new recruits into their future team long before their actual start date
   • A government department changed its approach to advertising jobs to reduce the risk that minority applicants drop out later in the process
   • An oil company combined HR data with facilities data to forecast real estate usage 3-5 years in the future

“If you measure it as 11 or 12 it doesn’t matter; what matters is, is it going up or down?”

Jeff Nelson and Nathan Adams, Aviva on ensuring action from analytics

The future of analytics

As chair, I get to throw in some fun ideas from other areas. Three that I mentioned were:

1.      Rapid intervention!

Adidas has reduced its fastest cycle time down to 2 hours from inventories dropping to changing its web marketing messages. Could HR adapt this to job postings?

2.      The future of HR: Uber?

Ricardo Semler has long advocated a more open and democratic workplace. He recently predicted the collapse of hierarchy in professional services as technology eliminated barriers to providing transactional services.

The same Uber principle could apply in HR: if managers can source recruits on the basis of external data and colleagues’ recommendations, will traditional recruitment go the same way as the mini-cab radio controller? If colleagues can allocate value-added project-by-project and evaluate reputation in the firm, if people reallocate themselves to projects rather than wait to be staffed [as at Liquid Organisation], could performance management, remuneration committees and staffing functions all disappear? HR would then deliver value where it has key knowledge such as employment law, key data such as on engagement, performance, learning and competencies, or via key skills such as strategic organisation design.

3.     Data-driven Organisation Design

My colleague Rupert Morrison has written a book connecting HR Analytics to its logical outcome: Data-Driven Organisation Design. The book, published by Kogan Page on 8th October, and endorsed by Peter Cheese of the CIPD sets out a step-by-step analytical data-driven methodology for making organisations more effective.

CIPD HR Analytics attendees can obtain it via: http://koganpage.com/ddod, entering the discount code: CIPDHRANALYTICS for 20% off.

“Visualisation can turn routine reporting into tantalising morsels”

Ben Nicholas, GlaxoSmithKline

How to get started with analytics:

The HR analytics community have considerable challenges in just getting the data into shape to use. Some simple steps that people talk about when getting the data into shape are documented in this lovely blog, on crunching the data:

http://simplystatistics.org/2014/06/13/what-i-do-when-i-get-a-new-data-set-as-told-through-tweets/?imm_mid=0d90c0&cmp=em-data-na-na-newsltr_20150923

You can also see more about getting data clean at:
http://blog.orgvue.com/7-steps-using-data-effectively/

How to do analytics? Some core HR & analytical tools:

There’s no doubt about it, HR people like to know what kit others have got. Tools that speakers talked about using included (with download links where I have them):

It is hugely encouraging to see HR beginning to lead business initiatives. I look forward to hearing everyone’s stories develop next year. If you are interested in learning more about HR analytics stay tuned for my HR analytics workshop with the CIPD on 10th February 2016 or check out OrgVue’s training courses

OrgVue Blog

Last Thursday, 8th of October 2015, marked the release of Rupert Morrison’s highly anticipated book, Data-driven Organization Design. With close to 200 attendees and talks from Peter Cheese, Chief Executive of the CIPD and Nathan Adams, HR Director at Aviva, the book has captured the minds of those looking to transform HR and OD functions.

It is clear why this book has garnered a lot of attention. It addresses one of today’s most endemic business challenges: how to use the wealth of data and information organisations possess to help employees to perform. This is not just performance in a business context, but also how to help people perform so they can meet their own ambitions.

Closing the Chasm

While functions such as IT, Finance, and Sales & Marketing have long capitalised on the art of data analytics for strategic decision-making, in most companies, the HR function still lags behind. Even for those prioritising analytics, the few that are furthest along their HR analytics journey have a long way to go. A recent study by Bersin (Deloitte)[1] revealed that while more than 60% of companies today are investing on HR analytics tools, only 14% have actually performed a rigorous statistical analysis of workforce data and a meagre 4% have the capability to perform predictive analytics. The rest are still grappling with chronic data problems, such as missing, outdated or inaccurate data, or are bogged down with producing ad-hoc reports to deliver standard operational metrics.

Consequently, as the book highlights, most business decisions today that directly impact employees have either been made on gut-feel instinct or financial data rather than people and process data. Morrison hammers home, no PowerPoint org chart or Excel spreadsheet have ever done justice to the job of organisation design or the employees they represent. In many ways, the current practice of organisational redesigns and transformations still neglect the people at the heart of them. They fail to focus change on maximising people potential and performance, something Peter Cheese articulated well at the launch. Given that people are an organisation’s greatest asset, such a reality is staggering and one which has to change. The challenge for organisations now is to close the chasm between organisational inputs and business performance outputs.

“This book puts into words what I’ve been trying to explain for years. Managers should read this book to become more data-driven; data-driven people should read it to understand the imperatives of management.”

Stéphane Hamel, Digital Analytics Thought Leader, Immeria

A Story of Transformation

This book will help HR and organisation design practitioners to cross this chasm, by empowering them with a practical toolkit and roadmap that can be used in high-level planning right down to everyday challenges. Whether carrying out a large or small-scale redesign, this book aims to provide a guide to ensure a successful transformation that will bring long-lasting impact. Nathan Adams, commented that such a guide has been a long time coming and one of the few books out there that addresses the day-to-day challenges of implementing an organisation design, not just the theory.

An example from the book on the impact of visualisation vs Excel Spreadsheets

The book is split into 3 sections: Micro, Macro and Making it Real. The first section focuses on the big picture, the strategy and the case for organisational change. Here, Morrison warns strongly of implementing a redesign without understanding the risks. Drawing on his own experiences of organisation design, he highlights just how fraught and risky a redesign can be. Instead, he recommends focusing on areas of the organisation which most need improvement and only undertaking a full redesign if there is an overwhelming case for change.

The Micro section outlines how practitioners can get the most out of their data and analytics to link the crucial elements of their business together. To get a “single version of the truth”- a starting point to drive business performance. Practitioners need to first understand the ‘as-is’ of their organisations, through visualisation and analysis, before they can successfully design their ‘to-be’ processes and structures. This is critical, since data, as the book describes is “emotive” and “can be threatening”. By bringing transparency of the organisational ‘as-is’, practitioners can minimise resistance to change and office politics.

Finally, what makes this book so valuable is its focus beyond the elements of good organisational design at the macro- and micro- level, but also its emphasis on making it real. This is the implementation and tracking of any organisational change project. The hardest and most tiring element of a redesign, and yet the most key when it comes to success.

“This book nails it. Honest and practical, it shows you how to deeply analyse and design an organization – and implement it.”

Nathan Adams, HR Director, Aviva

Data-driven Organization Design is set to be a hugely valuable resource for all HR and OD practitioners. It represents the start of a significant shift in thinking when it comes to delivering organisational effectiveness and understanding the impact of people in the organisation.

You can order the book here, using the code “DDMORR20” for a 20% discount

_{[1] Bersin, J. (2013) Big Data in Human Resources: A World of Haves And Have-Nots. Available at: http://www.forbes.com/sites/joshbersin/2013/10/07/big-data-in-human-resources-a-world-of-haves-and-have-nots/ (Accessed: 8 October 2015).}