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HR Analytics Archieven – AnalitiQs

People & Workforce Analytics Seminar 2018 – Day 1

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People & Workforce Analytics Seminar Brussels

Yesterday, I was at the 5th Icongroup People & Workforce Analytics Seminar in Brussels. Since the seminar is about HR Analytics (also known as People Analytics or data-driven HR), and consequently also about research and evidence, my colleague Gido van Puijenbroek opened the event with a small test: is it possible to sit on an inflated balloon? I won’t reveal the answer, but I promise it is safe to test it at home (or in a room with 100 people). Next to the balloon challenge, there is a number of less trivial lessons that I would like to share.

HR Analytics is a win for both the organisation and the employee

One of the main reasons that I love working in HR Analytics is that I can help organisations perform better by helping the individual employees in the organisation. Yesterday I noticed a lot of people other than HR Analytics practioners agree with me. In addition, I heard excellent cases that prove this point. There are two cases that I want to dive deeper into.

Charline Cleraux and Annelies Bartlema shared their story about the massive redeployment process that happened within ING Belgium. They considerably contributed to making that process a success by using HR Analytics. Even more impressive: there was not a single complaint about the process from within the organisation! They supported by creating an assessment based matching profile for each employee. Subsequently the profile supported the matching committee to make better funded matching decision between new jobs and incumbent employees. Optimizing this process served both the organisation and employees, since job fit was optimized, and the process was less prone to all kinds of biases.

Jan Billekens from Saint-Gobain found out, using an algorithm, that there are employees within the workforce that might be considered as talents, but for one or another reason are not in Saint-Gobain’s talent program. After this discovery all ‘hidden gems’ were reconsidered and if the recommendation from the algorithm could be echoed, the person was moved into the talent pool. Since the population is not static, the organisation goes through this cycle twice a year now. Obviously, this is in the interest of employees (potential optimization), but it also supports the organisation as it can now unlock all value from its human capital.

Employee experience should be the same as Customer Experience

Two tech companies, Salesforce and Cisco, showed the strength of giving employees the same experience as customers, thereby driving value creation through employee experience.

Louise O’Dwyer showed how Salesforce uses its own applications to capture the Voice of the Employee and how they use these data to create algorithms that support employees and managers in doing their job faster and better. For instance new hires are made aware of instruction and learning opportunities that have greatly benefitted previous new hires that were similar to them. Managers get push notifications informing them what a new hire should be able to do after a certain period and what interventions they could consider to improve the learning curve. All these things lead to 90% of the employees being engaged and promoting the organisation to clients and potential hires.

Amanda Diston of Cisco showed us the impact of the proposition they make to their (future) employees. Making this proposition and sticking to it, increases employee engagement. How do they know if the organisation sticks to its promises? As an example, employees assess their leaders every quarter, leaders are provided with this input (data) and are supposed to follow up on the feedback.

Gido van Puijenbroek

 

Use data as a catalyst for data quality

As Oliver Kasper of Swarovski said: Everybody loves good data quality, but nobody loves working on data quality. Consequently, it is required to create a rinsing mechanism.

Suggestion 1: the best way to find out what needs to be improved and actually getting data quality up, is by simply using the data. As Peter Hartman of Getinge told us, using the data you have is always better than just another guess. Moreover, by using the data and making the state of the data visible, even if the data is not even remotely correct, a feedback loop can be ignited.

Suggestion 2 came from Giles Slinger: after each data run/project, do send out a data error/quality report, so the data quality can be improved.

These practices help towards a (more) swift delivery of the next project, as there is probably less data cleansing to do and it increases the chance of getting killer insights.

Be picky

Like the previous lesson this one is an evergreen. Multiple speakers, including ABN AMRO’s Stijn de Vries, put emphasis on the importance of selecting HR Analytics projects that solve true business problems and have strong stakeholder commitment. It was even encouraged to be picky when taking on projects. After all, time can only be spend once and the more impact generated the stronger data driven HR is embedded in the organisation in the long run.

Make yourself redundant ASAP!

The last but not the least lesson I would like to share is about redundancy. Stefaan Rodts of Aegon revealed his ultimate goal is to get released from his HR Analytics Director position within a couple of years. Not for any bad reason, but because his aim is to make the HR function data driven. In his view most HR employees should ultimately have a data and structured problem-solving mindset and they should be able to interpret reports and insights from analyses. In such a perfect world each company would still need data scientists, BI specialist, researchers, but HR would work directly with them rather than via or with an HR Analytics Translator.

All in all, day 1 was very interesting and exciting and I’m looking forward to day 2 of the event!

Also read: Icongroup People & Workforce Analytics Seminar 2018 – Day 2

Author:

Teun ter Welle

Teun ter Welle

Data Scientist AnalitiQs

Behind the Steering Wheel at Deutsche Telekom

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In November Icongroup will host the People and Workforce Analytics Seminar in Brussels. Gido van Puijenbroek (AnalitiQs) is chair of the seminar and in the run-up to the event he will interview several speakers, such as ING and NS (Dutch Railways). This time around Gido has had the pleasure to speak with Michael Rubas who is Senior Vice President of HR Planning, IT and Operations at Deutsche Telekom: “We don’t have a crystal ball, but we want to get firmly behind the steering wheel.”

AnalitiQs interviews speaker Michael Rubas about HR analytics

In November you will be speaking at the People & Workforce Analytics Seminar in Brussels. What are your expectations for this event?

“Of course, good food and a nice Belgian beer. But more seriously, I hope to have interesting conversations with and gain insights from other companies and practitioners. I’m particularly interested to learn more about questions which got answered through HR Analytics and had true business impact. Ideally not on an abstract or infrastructural level, but truly at a case level which created value.”

Could you give a sneak peek into your presentation ‘Skill up: We Create the Workforce of The Future’?

“First of all, I will point out that we are on an HR Analytics journey at Deutsche Telekom, like many other organisations. I will touch on topics such as infrastructure and legislation. From this framework I will make a deep dive into a couple of cases, for example how does the network of leaders influence their performance?”

I’m very curious about your cases, but before we go into the stuff you and your team are doing, could you tell more about yourself?

“Sure! In the course of my career I have spent about 50% of my time in IT within the B2B industry. The other half of my time has gone into HR And People Management. These two experiences led to my personal passion. Bringing ‘people’ to the business and bringing ‘technology’ to HR. In the world we currently live in, both are important topics and enablers for value creation. Within that space Workforce Analytics is an exciting topic, since it is both people and technology focused.”

Two interesting features of your presentation are the use of external big data and data about skills. Could you elaborate on the relevance of these two features?

“Within Deutsche Telekom the quantitative part of Strategic Workforce Planning, FTE and total workforce costs, has a very reasonable level of maturity. We can match actuals and forecast pretty well. It’s part of our DNA of the constant transformation towards more efficiency.

Next to becoming more efficient we also looking at new business opportunities/innovation since this will keep us relevant. The need for innovation makes skills planning essential and a new objective, because it is pivotal to understand whether new markets can be opened up. Another driver behind this trend is the awareness that we can’t bring in all these people with new skills from the outside because of labour market shortages, and by offering our employees opportunities we want to stimulate corporate citizenship.

So that is the ‘why’ behind skills planning. The ‘how’ is extremely difficult because no one can exactly predict what will happen in the future. After all, we don’t have a crystal ball.

To mitigate for this, we do our best and partner with those positioned best, such as the Strategy department. They can provide information about trends, likelihood of certain developments and potential impact. In addition, we have started using external big data. We scrape/crawl the data from the internet and use the data to inform ourselves about questions like: what kind of skills, for example 5G or cloud computing, are other competitors looking for and how many people are on the market for this kind of positions? Having these insights helps for discussions, for instance: why do we search for fewer cloud computing people than competitor X? Why do other organizations act differently?

Ultimately, we want to get out of the reactive approach and we want to get firmly behind the steering wheel, without claiming we have a crystal ball.”

On your LinkedIn profile it is mentioned you are responsible for driving customer centricity of the HR organization. Can you share how you use data to establish this?

“HR has a tendency to live in its own world and to set its own priorities. As a result, the customer wasn’t really happy in the past. At Deutsche Telekom we now start with two questions: what does the customer need? How do we optimize business value from an HR perspective? From there we select a limited number of topics.

For the selected topics, we consider how to effectively implement them. For this purpose, we use design thinking, including journey mapping: how do customers inform themselves, how do customers interact with us and what are the moments that matter? Also, we involve our customers early in the process. We want to measure four things: client satisfaction, promotion, adoption and effort. The data we use in this space is a combination of survey data, for example satisfaction and promotion, and system log data for adoption, for example the number of people who have sent out a feedback form.

We look at this data at an aggregated level because of privacy concerns, but that is still quite interesting and insightful. The dimensions we can use depend on the agreement with the workers council. For instance, for the correlation between perceived leadership and team cohesion, we were allowed to analyse patterns such as age or gender using data from the engagement survey.”

Could you elaborate on a use case which you are proud of in terms of impact created and/or innovative methods used?

“That would be the leadership performance model that I mentioned earlier and which I will also discuss in November during the seminar. Our CEO has introduced three leadership principles, one of them is collaboration. This principle ran the risk of being perceived as a fluffy principle and as typical HR stuff. Nevertheless it is a paramount principle since in today’s world, no one is able to create products in a silo. Therefore, collaboration is truly important and represents business value. We were able to show the relationship between collaboration and value creation. Consequently, we have mitigated the risk and no we can link people and HR unequivocally with business outcomes.”

Creating and measuring the ROI of HR analytics is a concern that many leaders in this field ponder about as it is thought to be a requirement for long term relevance of the field. What is your view on this topic?

“ROI is challenging. To give an example: our most expensive investments are in reporting infrastructure. The ROI of good reports is hard to establish. So rather than ROI calculations we use a different measure for success. We look at what happens after presenting insights. Do we discuss insights and say we find them interesting but then go back to work? Then there is a negative ROI. If we discuss insights, say we find them interesting and follow through by changing practices in accordance with the insights, then there is a positive ROI.”

One of the requirements of making people decisions fact-based is a data savvy HR function where data is not a mere after thought, but truly integrated in the way of working. HR people tend to be not the most fact-based people. Is this something you recognize and if so how should HR leaders anticipate on this?

“I do recognize this. As soon as people end up in an HR department it seems like they immediately switch to a mode where they inform themselves by observations and subsequently act or advise on it. I believe we need more social scientists and anthropologists in HR. These people are trained in observing, continue from there with collecting data and only then derive conclusions. If we want to be true people experts, we have to recruit these profiles.”

Finally, a lot has been written and said about the GDPR. What are your preliminary reflections on the new legislation?

“Not an expert on other countries, but for sure the GDPR led to standardization and this is helpful in terms of expectation management. In Germany work councils have a strong position. Therefore, mutual trust and dialogue are extremely important. If there is a good relationship and we also look at the employee advantages of analytics, many things are possible. However, using a tool such as Humanyze is unimaginable in our organization due to opinions. So legal framework is converging, but opinions about where to draw the line might still set Germany apart.”

Want to learn more about Michael’s insights?
Don’t miss his presentation ‘Skill up: We Create the Workforce of The Future’ on Thursday November 22nd at the People & Workforce Analytics Seminar in Brussels.

Exclusive discount
Gido van Puijenbroek (AnalitiQs) will be hosting day 1 of the event. We would like to offer you an exclusive discount of 100 euros on your ticket. Are you interested? Please send us an e-mail to receive your discount code. See you in Brussels!

Author:

Gido van Puijenbroek

Gido van Puijenbroek

Managing Director AnalitiQs

Ethics & People Analytics

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Charline Cleraux (top) and Annelies Bartlema (bottom) are both data scientists at ING Belgium and will be speaking at the Icongroup People & Workforce Analytics Seminar in November 2018. As AnalitiQs (Gido van Puijenbroek) is chairing day 1 of the event, Gido spoke to them about People Analytics at ING, developments within the field and their interest in Ethics in relation to analytics. “People Analytics has proven its value within ING and is now considered a given in our way of working.”

Charline Cleraux - Data Scientist, ING Belgium (click to open)

Charline leads People Analytics projects for ING Belgium with a specific focus on guiding the organization through business transformation.

Her vast experience includes data duplication, marketing analytics and fraud detection as a consultant, and as a statistical and IT Security Researcher for an American governmental research institute.

Annelies Bartlema - Data Scientist, ING Belgium (click to open)

Annelies has a university degree in experimental and mathematical psychology, and three years practical experience as a general data scientist.

At ING, she combines her passion for data with her passion for people. Leading various people analytics projects, she pushes the people analytics practice and adds value to the business through data driven decision making.

What are your expectations for the People & Workforce Analytics Seminar?

For us this is an opportunity to share  some of the work we did. In addition, we are also going to the event to learn from other companies. We are very curious about the experiences of other People Analytics professionals!”

Could you give a sneak peek into your presentation – what will you be talking about?

“As you might have heard ING is going through a business transformation. In this transformation People Analytics is one of the key enabling elements. We will talk about how People Analytics is guiding the redeployment of people. In addition, we are planning to share one or two other cases.”

Can you give us a summarized overview on the development of People Analytics at ING Belgium?

“ING Belgium initiated People Analytics in 2015 via pilot cases. The sweetspot was to find business leaders with a burning question or believe where People Analytics could respond. At first the team was completely separated from all other reporting activities. We found this split important in order to concentrate on the development of People Analytics without the pressure of (mandatory) reporting. With 1 data scientist in the team we grew maturity by performing projects in the field of recruiting, reward and development. Last year the team expanded with an additional scientist and we merged reporting, data management and People Analytics into one bigger team. People Analytics has proven its value within ING and is considered a given in our way of working.”

Market research from AnalitiQs shows adoption of Insight Driven HR is gradually growing in the Netherlands, but the gap between leaders and followers seems to be growing as well. Does this also apply to the Belgium market?

“We can see that awareness about this topic is growing in the Belgian market. The Netherlands is probably a bit more advanced. However, the gap that AnalitiQs has identified doesn’t sound entirely irrational. In the end every organisation which aspires to be successful with People Analytics requires solid data management practices as a foundation to build on. Putting data management in place is a huge task, but once nailed, organisations can start building momentum. Since the frontrunners started earlier to now reap the benefits and can build more momentum.”

You previously mentioned that you would like to discuss the relationship between Ethics and People Analytics. Why do you find this an intriguing relationship?

“When we talk about our profession we notice people often assume we do unethical things, e.g. algorithms that suggest who to fire. Obviously, that is not what we do. Those assumptions made us interested in the relationship between Ethics and Analytics and we would like to learn from practices within other organisations.

At ING we have solid practices in place to prevent unethical applications of People Analytics and we want to use People Analytics in a positive way for the organisation and the employees. Therefore, we always do the things that the law requires us to do, for example a Privacy Impact Assessment (PIA), reporting in such a way that individuals can’t be identified.

We also go beyond that. For instance, we do a ‘front page’ check: what would happen if this would appear on the front page of a newspaper? It’s an interesting way to investigate the ethical perspective of a proposed project. Also, we have declared some data as out of scope for People Analytics, e.g. marital status. As such we make a triangular judgement (legal, ethics, opinions) before we commence and before publishing insights.”

Out of the box things other organizations do to safeguard Ethics in relation to People Analytics (click to open)

  • Make all project output available to all employees
  • Appoint an Ethics officer with whom People Analytics professionals and others in the organization can consult
  • Organize an People Analytics sound board in which employees participate and assess ideas on trust and social acceptability

Many marketing departments buy data sets which are generated by companies like Experian, EDM, 4Orange, PostNL data solutions and contain many data points at household level, e.g. number of kids, age bucket kids fall in, educational level adults, property value, etc. Would it be ethical to use such data for People Analytics purposes in your view?

“First of all, we wonder if this is still allowed within the GDPR (legal check). More importantly, the suggested practice doesn’t feel right (ethics and opinion check). Lastly, Marketing is different from HR in a sense that the relationship between a company and a client/prospect is a free one and one that is easy to terminate, whereas in HR there is less of a voluntary relationship (employer – employee).”

On to a different topic, McKinsey recently introduced the role/function ‘Analytics Translator’. What is your view on such a role, do you think it is required to get the full value out of Analytics?

“The skills such a person brings are certainly required. However, we’re not entirely sure whether it requires a separate role. Ideally the Data Scientist should have strong business skills and have a solid understanding of the context (s)he is working in. Those people might not be largely available. In such a situation it is about composing a balanced team and an Analytics Translator role could be really helpful.”

What exactly is an Analytics Translator? (click to open)

“To understand more about what translators are, it’s important to first understand what they aren’t. Translators are neither data architects nor data engineers. They’re not even necessarily dedicated analytics professionals, and they don’t possess deep technical expertise in programming or modeling.

Instead, translators play a critical role in bridging the technical expertise of data engineers and data scientists with the operational expertise of marketing, supply chain, manufacturing, risk, and other frontline managers. In their role, translators help ensure that the deep insights generated through sophisticated analytics translate into impact at scale in an organization. By 2026, the McKinsey Global Institute estimates that demand for translators in the United States alone may reach two to four million.”

Source: McKinsey

Organizational Network Analysis (ONA) and Continuous Listening (CL) are hot topics within People Analytics. Are these topics also trending within ING Belgium?

“Yes! Continuous Listening is a big topic because of the transformation. How do people feel? What can be improved? To get a feel for what is going on we do 1 big survey every other year and we combine that with pulse checks. These pulse checks are executed at a higher pace, contain shorter questionnaires and they are being send to random samples.

Organizational Network Analysis is a topic of interest. We are for instance interested in the collaboration between teams. However, we haven’t done anything on the topic so far yet. Main challenge there is to find a practical way to do it so it that also passes the triangular test (legal, Ethics, opinion).”

Want to learn more about the experiences of Charline and Annelies?
Don’t miss their presentation ‘Business Transformation driven by People Analytics’ on Wednesday November 21st at the People & Workforce Analytics Seminar in Brussels.

Exclusive discount
Gido van Puijenbroek (AnalitiQs) will be hosting day 1 of the event. We would like to offer you an exclusive discount of 100 euros on your ticket. Are you interested? Please send us an e-mail to receive your discount code. See you in Brussels!

Author:

Gido van Puijenbroek

Gido van Puijenbroek

Managing Director AnalitiQs

HR-analytics

By | Boeken | No Comments

HR-analytics wordt vaak in één adem genoemd met e-HRM systemen en business software die organisaties een schat aan informatie leveren over hun human capital. Maar wat is HR-analytics nu precies en – vooral – wat kun/moet je ermee als HR-professional?

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HR-managers vaker tevreden over gebruik HR-analytics

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HR-MANAGERS ZIJN VAKER TEVREDEN OVER HET GEBRUIK VAN HR-ANALYTICS

De afgelopen jaren inventariseerden wij onder Nederlandse HR-managers de bekendheid met en het toepassen van HR-analytics in Nederlandse organisaties. In 2018 is het HR-analytics onderzoek opnieuw uitgevoerd door AnalitiQs in samenwerking met HR Academy. Wat zijn de belangrijkste inzichten?

De HR-managers zijn steeds meer tevreden* over het gebruik van HR-analytics binnen de organisatie. Waar slechts 1 op de 9 (12%) HR-managers in 2016 het gebruik van HR-analytics beoordeelde met een zeven of hoger, is dit nu 2 op de 9 (22%) HR-managers. We zijn er echter nog niet, zo blijkt uit het gemiddelde dat nog steeds onder de vijf ligt. Dit verschil komt met name doordat managers minder vaak een 6 geven (15% in plaats van 27%).

HR-analytics wordt niet vaker maar wel beter ingezet

De enigszins hogere tevredenheid over het gebruik van HR-analytics uit zich met name in een stijging in het gebruik van metrics, maar niet zozeer in het gebruik van analytics. Afgelopen jaar heeft 77% gebruikgemaakt van metrics (al dan niet in combinatie met analytics). Dit is een duidelijke stijging ten opzichte van eerdere jaren, toen het rond de 70% schommelde. In totaal heeft 14% gebruikgemaakt van zowel metrics als analytics. Dit is vergelijkbaar met voorgaande jaren.

Figuur 1 - Mate waarin organisaties Metrics en analytics gebruiken in 2015, 2016, 2017 en 2018

Figuur 1 – Mate waarin organisaties Metrics en analytics gebruiken in 2015, 2016, 2017 en 2018

 

Dat metrics vaak worden gebruikt, blijkt ook uit de zaken die momenteel goed gaan met betrekking tot HR-analytics. Zo worden rapportages het meest genoemd (27%). Daarnaast worden data(kwaliteit) en opslag en bewustwording relatief vaak genoemd.

Figuur 2. Top vijf van de genoemde zaken die goed gaan met betrekking tot HR-analytics.

Figuur 2 – Top 5 van de genoemde zaken die goed gaan met betrekking tot HR-analytics

 

Stabiele toename in het verwachte gebruik van HR-analytics

De huidige verwachting is dat over 12 maanden 91% metrics zal gaan gebruiken. Dit is iets meer dan de afgelopen 2 jaren, maar minder dan de verwachting die men in 2015 had (94%). Van de mensen die verwachten metrics te gebruiken over 12 maanden, verwacht 66% ook analytics te gebruiken. Dit is eveneens meer dan de afgelopen twee jaar, maar minder dan in 2015 (72%). Echter, waar in 2015 de verwachting duidelijk werd overschat, lijkt er nu een reële stijging in de verwachting te zijn.

Figuur 3 - Verwacht gebruik van HR analytics over 12 maanden in 2015, 2016, 2017 en 2018

Figuur 3 – Verwacht gebruik van HR analytics over 12 maanden in 2015, 2016, 2017 en 2018

 

Tijd is de belangrijkste uitdaging voor gebruik van HR-analytics

Om dit te bereiken, moeten enkele uitdagingen worden overwonnen. De belangrijkste uitdaging is het zorgen voor voldoende tijd. Ruim drie op de tien respondenten (31%) geeft aan dat dit een belemmering vormt voor het gebruik van HR-analytics. Daarnaast zijn het vormen van een HR-analytics visie en HR-analytics als prioriteit stellen belangrijke belemmeringen.

Competenties, tools en systemen worden ook vaak als barrière gezien. Opvallend is wel dat deze zaken minder vaak worden benoemd dan vorig jaar. Wellicht dat vergrootte kennis ervoor heeft gezorgd dat er betere tools en systemen zijn óf dat inzichtelijk is gemaakt dat met de huidige tools en systemen ook goed HR-analytics kan worden toegepast.

Figuur 4 - Relatief aantal belemmeringen voor het gebruik van HR-analytics in 2017 en 2018

Figuur 4 – Relatief aantal belemmeringen voor het gebruik van HR-analytics in 2017 en 2018

 

Zodoende kan worden gezegd dat er steeds meer metrics worden gebruikt in organisaties en dat dit er toe heeft geleid dat HR-managers vaker (zeer) tevreden zijn over het gebruik van HR-analytics. Daarnaast lijken de competenties voor het gebruik van HR-analytics te zijn vergroot. Belangrijke kanttekening is dat tijd nu nog vaak een struikelblok blijkt te zijn.

Wil je meer weten over het HR-analytics onderzoek? Neem dan contact met ons op!

* Tevredenheid gemeten op een schaal van 0 t/m 10.

Gido @ People Analytics World – Day 2

By | Blog, Geen onderdeel van een categorie, HR | No Comments

Gido van Puijenbroek

Finding an affordable, but decent place to stay in London is not an easy task. As an experiment I made a reservation at the easyHotel, family of easyJet. Perhaps I was a bit naive, but for business purposes it might not be the most suited hotel. As a result of my experiment I arrived at the conference less energetic than the day before and in a wrinkled shirt, lol. Luckily the presentations I attended were very interesting, so I didn’t have hinderance from my little experiment.

Nicky Clement – Data storytelling and demonstrating ROI from people analytics

A common theme at the conference, for those just starting, but also for those ahead of the curve, is the conversion of insights into action and true ROI.

Nicky heads up a team of 6. Which, in my view, is not an awful lot if you consider the headcount and geographic spread of Unilever. Subsequently one of the key questions for her and her team became: “how to maximize reach and thereby action with limited resources?”

At Unilever they have applied different techniques to create reach. They have lifted the floor by educating HR BP’s just so they can make better use of the available toolbox. They have pushed the ceiling up by working one on one with leaders and turning them into “converts”, for instance by sitting down with them and answering their questions on the fly with the Tableau people dashboard. Moreover, they create a provocation pack for senior leaders every once in a while to get and stay on the radar.

Apart from above mentioned items one other, seemingly simple, thing stood out. They have created a community. At the core of the community is the people analytics team. In the second ring are cluster leads. I imagine these to be ambassadors/points of contact within a BU. And in the outer ring are volunteers with a passion and/or expertise in the people analytics field. By building and maintaining the community the people analytics team has been able to make waves and turn a 6 person team into a 50+ coalition.

Nicky Clement

Vanessa Lammers – Engagement check-ins, a pro-active approach to enhance employee experience and retention

Continuous listening, together with Network Analytics, were the trending topics at the conference. The presentation from Vanessa shed a light on how Nestlé Waters went about in getting a better feel for the sentiment in the organisation.

The team started out with creating a research strategy. For instance, addressing questions like “which questions should we answer through research?”, “what to investigate in a qualitative and/or quantitative fashion?”, “which workforce segments should we target?” and “how can we create leading instead of lacking indicators?”.

To illustrate how they have answered some of these questions it is interesting to note that nowadays Nestlé Waters combines quantitative with qualitative research, low frequency (annual engagement survey) with high frequency (short pulse surveys about particular topics), they target segments of the workforce where high turnover would cause high impact (think scarce labour market, high performance and potential scores), they hold stay interviews (leading indicator) next to exit interviews (lagging indicator).

Apart from strategy they also diligently worked on research design because asking poor questions has an inverse impact on the value that can be created. This sounds obvious, but from experience I can tell many organisations let HR professionals design surveys, whereas these people have never been trained in research methods. To more vividly paint the survey design picture: instead of asking “what are the reasons for leaving?” they now ask top X reasons. Alternatively, a follow up question on “what are the reasons for leaving?” could have been “rank the earlier provided reasons for leaving”.

Nicky Clement

Swati Chawla – HR-analytics to drive business decisions

13 Asian countries, 150 meetings and 8 months of work. That is the context in which Swati executed her project. But it was worth it! Not only did the project successfully answer the business question “how can we grow sales?”, it also answered the underlying research questions “how can we organise, manage and utilise the salesforce?” and put HR-analytics more firmly on the map.

In my opinion the beauty of this case is twofold. First, only a handful of relatively simple statistical methods have been used, e.g. probability analysis. All else was based on metrics like sales and profit per sales, sales and profit per FTE, span of control, contribution to profit by employee tenure and scenario planning. Second, I can tell from experience almost all companies would have the vast majority of all input data available in existing systems and/or spreadsheets. The only thing that Swati and stakeholders had to manually create was a task/time allocation matrix for the sales staff in various markets.

On the back of this case a quote I picked up on day 1 popped back up in my mind: “the impact of analytics is oftentimes inversely related to the complexity of methods used”. Not sure if this is always true, but probably good to reflect on this quote when designing a project.

Another thought that surfaced and might be worth pondering about on the back of this case: shouldn’t all organisations have a HR controller in their team, just like finance has business controllers?

Steve Bianchi – The successful long game

Where I was starting to think network analysis is something everyone talks about it, but few have experience, Steve Bianchi appeared on stage.

He presented a case in which he and his team had scraped LinkedIn data for a number of purposes. (1) Calibrate job specs. If, based on characteristics in the job specs, profiles were returned that insufficiently matched, the job profile was adjusted. (2) Find candidates. As soon as there was a robust job spec the system would return interesting candidates. (3) Leverage the network of the workforce. If candidates had a connection with one of the employees that already worked at the organisation the employee could earn a referral fee in case of a match.

Steve Bianchi
Unfortunately, LinkedIn doesn’t share its data any longer and GDPR will shortly kick in, so by now this example can’t be (easily) replicated any longer. In addition, the case above is only feasible if an organisation is sufficient in data management. And this doesn’t always hold true, because within HR the following lesson is little recognized: “great information management enables great management information”.

Other takeaways

Next to my takeaways from the presentation there are several common themes that I did not incorporate yet. Below a succinct run down.

  • GDPR & Ethics and the Extended Workforce (flex/core) are still hot topics. Perhaps the latter is one of the reasons why network analytics is hot.
  • The Analytics Translator is a must have in all HR-analytics teams. The role is instrumental in educating HR peers and Line Management which helps to create impact. In addition, the role can shape and manage projects in a dedicated and hence more effective way. The function can turn the insights into compelling nuggets of information for customers (e.g. through visualisation and storytelling).
  • As continuous listening becomes more common, text and perhaps even speech analytics will receive a lot of attention going forward.

Also read: Gido @ People Analytics World – Day 1

Gido @ People Analytics World – Day 1

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Gido van Puijenbroek

Most mornings I don’t wake up excited at 6am. However, yesterday was different. Not only was I bound for my old home town, London, but I was also going to enjoy two full days of People Analytics (a.k.a. data driven HR, HR-analytics, Workforce analytics, HR Intelligence, etc).

So… what are my main take aways from the presentations I attended on day 1 of People Analytics World 2018?

People Analytics World London 1

Bernard Marr | Creating A Super-Intelligent HR Function – 9 Lessons We Can Learn from Elite Sports Teams

Bernard pointed out an interesting paradox. Where athletes are happy to give their data to data scientists – as it helps them to respond quicker, learn faster and hence perform better – employees are reluctant to share data with the organisation they work for, whereas they could reap the same benefits.

Another interesting nugget form this presentation: there is lots of talk about big data, however, why not keep it simple and start with asking the question: “What is the right data, i.e. quality and usefulness, for analysis?”

Brydie Lear & Eva Oudemans | From “It’s complicated” to Corporate Cupid

ING is one of the front runners in HR-analytics, so for me, this was one of the presentations I was looking forward to most. Not only did ING present two highly interesting case studies (hence the title of their presentation), they also shared how they select their projects. As I get the question – “how do we select a topic to start with?” – a lot from organisations which are about to embark on their HR-analytics journey.

Here is how ING goes about in selecting a project: first they develop ideas (these could come from the team itself or a variety of stakeholders), secondly they check for business interest, then an assignment is fleshed out, subsequently a target is formulated and lastly they commence the analytics execution cycle. Next to this process it is important to mention that all ideas are tested against eight principles: strategic alignment, importance / urgency, number of FTE’s impacted (the more the better), mature business performance data, access to data, explicit and agreed ROI upfront, strong leadership and last but not least local ownership & resources.

People Analytics World 2018 2

Subhadra Dutta | Competency Development… With Data!?

Twitter is Silicon Valley based and constantly heavily involved in the war for talent. Therefore, employee experience is key. As such four years ago an HR-analytics team has been created to enhance employee experience. Today they are six strong. Like many other companies the central analytics team does not focus on operational reporting. Metrics, advanced analytics, assessments and research are included however. The inclusion of the latter two is something I hear more and more often (trend?).

What was interesting other than headcount numbers and scope? The importance of understanding the competencies of your workforce was once more underlined.

Without competencies there is no strategic workforce planning, effective development, effective leadership, robust selection, or in other words no optimised organisational performance! Therefore, a shout out from me to all HR departments: if you haven’t already done so…. create a competency model, assess the workforce / critical segments of the workforce and use the data for the abovementioned purposes (yes, even though it can initially be a labour intensive exercise). They do really cool stuff at Twitter, how inspiring!

People Analytics World 2018 3

Peter Cheese | Embracing Analytics: The Opportunities and Challenges for HR

Peter was the perfect presenter after the break. High paced combined with provoking statements.

Consider this one: “HR brings too much PowerPoint and not enough Excel”. Agree or disagree? Where are you on the spectrum? It would be preaching to the quire if I would give my opinion.

Another interesting observation: “If we want to move away from shareholder value, HR should develop a way to make intangible assets (e.g. people) measurable.

Morten Kamp Andersen | Impact Throughout the Organisation: Using People Analytics to Guide and Improve Change Management

Morten is a man on a mission. The mission is to widen the scope of people analytics. Rather than focusing on two areas, namely: (1) making better HR decisions, e.g. improving the recruitment process, or (2) making better business decisions, e.g. what type of sales person sells most, he argues a third dimension should be added. This dimension should be about “helping internal projects succeed”. As an example he painted how the introduction of a new CRM could be done with less resistance and better adoption. At AnalitiQs we have very positive first-hand experience with the power of culture change and analytics, so I would like to echo Morten’s plea.

Laurie Bassi | Smarter Employee Engagement Analytics

It is always hard to present at the end of a full day. Nevertheless, Laurie did know how to trigger the audience and left us with a recommendation. In her view one essential step in creating high impact outcomes is “mass customization of findings”. Put differently, each unit / manager should get customised recommendations, rather than creating one recommendation at company level. Not sure if it is always feasible within project constraints (budget, timelines, etc.), but something that could help to drive adoption of insights, and therefore to consider when fleshing out an analytics project plan.

Also read: Gido @ People Analytics World – Day 2

Word ook een Power BI Ninja!

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Auteur: Teun ter Welle

Power-BI-gebruikersdag-2018-2

 

Zaterdag 24 maart heb ik met mijn collega’s Jilske en Irma de Power BI Gebruikersdag 2018 in Utrecht bijgewoond. Power BI is een Business Intelligence-tool waarmee je data makkelijk kan visualiseren en dashboards kan maken voor verschillende devices. Zoals de naam doet vermoeden, stond deze dag vooral in het teken van het gebruik van Power BI.

Bij AnalitiQs zijn we gespecialiseerd in het visualiseren van data in Tableau, Power BI en Qlikview. Ik werk voornamelijk met Tableau, maar gebruik steeds vaker Power BI. Aangezien deze tool zich in rap tempo ontwikkelt, was ik benieuwd naar best practices en de laatste ontwikkelingen.

Aan de hand van technische sessies, praktijkverhalen en nieuwe ontwikkelingen werd getoond hoe je het maximale uit deze tool kunt halen. Tijdens dit congres deelden vakgenoten van o.a. Heineken, InHolland, Widex en Microsoft hun ervaringen over het maken van dashboards/rapportages in het algemeen en Power BI in het bijzonder.

Wat heeft deze dag mij gebracht? Verschillende interessante onderwerpen passeerden de revue. Denk hierbij aan het verbeteren van performance bij data verwerking, ervoor zorgen dat de eindgebruiker meer uit het dashboard haalt wat jij voor hem of haar hebt gemaakt en het maken van een dashboard dat zowel een lust voor het oog is als praktisch voor de eindgebruiker is.

De belangrijkste tips & tricks heb ik hieronder voor je op een rijtje gezet. Er is voor ieder wat wils: van beginner tot ninja, en van het optimaal ondersteunen van de eindgebruiker tot het best visualiseren en verwerken van de data.

Met ruim 400 bezoekers en inspirerende sprekers kan met recht gezegd worden dat dit een waardevol evenement is voor Power BI gebruikers. Ik ga er volgend jaar zeker weer naar toe! Ook als ik dan een Power BI ninja ben geworden.

Power-BI-gebruikersdag-2018

Optimaal ondersteunen van eindgebruikers

  • Geef workshops aan de eindgebruikers zodat de eindgebruikers niet alleen doen zoals ze het altijd hebben gedaan, maar ook de extra functionaliteit en dus waarde uit het dashboard halen.
  • Stem je rapport af op de eindgebruiker: toon je de cijfers en grafieken of slechts de uitkomsten van enkele KPI’s?
  • Doorgaans willen organisaties, in eerste instantie, rapportages zoals ze gewend zijn ontvangen. Breng daarom voorzichtig verandering aan. Soms is het goed om eerst oude rapportages na te bouwen in een nieuwe tool en deze langzaam uit te breiden.
  • Zorg voor een meldpunt of vraagbak bestaande uit diverse consultants die geraadpleegd kunnen worden door de eindgebruiker. Zo weten eindgebruikers bij wie ze moeten zijn als ze een vraag hebben en krijgen een goed afgestemd en duidelijk antwoord.
  • Stem de look en feel van het rapport af op de organisatie voor wie het rapport wordt gebouwd. Dit geldt niet alleen voor het kleurgebruik, maar ook bijvoorbeeld voor de locatie van het logo en de filters. Als er verschillende rapporten worden gemaakt, is het verstandig om hier richtlijnen voor te maken.
  • Als de eindgebruiker ook op zijn/haar telefoon het dashboard wil inzien, maak het dashboard dan mobile friendly. Het is aan te raden om hier bij de start van bouwen rekening mee te houden.

Power BI

  • Met Power BI kan je dashboards maken (of voor iemand anders dit doen) met grafieken uit verschillende rapporten. Let hierbij op dat de filters hetzelfde blijven. Dus als je op “Maart 2018” filtert omdat dit de laatste maand is, dan blijft dit de volgende maand ook “Maart 2018”. Een simpele workaround is door de filter op “laatste maand” te zetten of een variabele “laatste maand” aan te maken en hierop te filteren.
  • Het is mogelijk om de default settings aan te passen met .json-bestanden. Bekijk hoe dit werkt
  • Je kunt template bestanden (.pbit) voor thema’s maken en opslaan, vergelijkbaar met een thema in PowerPoint.
  • Het is inmiddels mogelijk om de slicer van een pagina te synchroniseren met andere pagina’s! Let op: Power BI synchroniseert automatisch slicers met dezelfde naam. Is dit niet wenselijk? Geef de slicer dan een andere naam.
  • In Power BI kun je een grafiek gebruiken als tooltip voor een andere grafiek. Dus als je met je muis sleept over een verzuimpercentage trendlijn kun je een grafiek tonen met daarin de percentages kort, midden en lang verzuim. Zo kun je eenvoudig extra inzichten krijgen wanneer dit gewenst is.

Data source

  • Snelheid van het verwerken van de data is afhankelijk van de databron. Power Query is intelligent en kan ‘praten’ met de databron. Daardoor verwerkt Power Query de data sneller van slimme databronnen als SQL, maar trager als de databron csv-bestanden zijn.
  • Power Query verwerkt bij een tabel kolommen makkelijker dan rijen. Dit geldt in het bijzonder voor unieke waarden. Maak deze, waar mogelijk, niet meer uniek door de rij uit te splitsen. Denk hierbij aan een waarde waarin zowel de datum als de tijd staat (dd/mm/yyyy hh:mm). Deze kan je beter in waarden over 2 kolommen: (1) datum (dd/mm/yyyy), en (2) tijd (hh:mm). Als tijd helemaal niet nodig is, dan kun je deze zelfs beter verwijderen.

Auteur:

Teun ter Welle

Teun ter Welle

Data Scientist AnalitiQs

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