Struggling with Your Analytics Reputation?

As someone who helps clients with analytical subjects, I see the full spectrum of people’s successes and frustrations. Often, people will confidentially share their struggles with their external consultant when they wish to have a sounding board but they don’t feel comfortable having the discussion with their colleagues or leadership.

It is also not unusual after I give a speech at a conference, to have analytical professionals walk up to me and say, “Thank you, you’ve helped validate what I’ve been trying to accomplish at my own company.” It is comforting to these people to know that they are on the right track, even if they haven’t reached the point where their own colleagues understand the bigger picture and see the value of analytics. At this point, they are feeling alone on an island with no supporters, especially if they are the only analyst within their functional area.

Some people translate their frustrations into a need to organize and define. Over the years, I’ve seen many articles of people attempting to define analytical terms and / or analytical job titles. One author suggested that you can’t be a Data Scientist unless you are versed in applying scientific techniques like hypothesis testing. I guarantee you that the people in HR writing job descriptions and using the title of Data Scientist will never worry about the suggested definitions on the internet. In the real world, HR will do the best it can when writing technical job descriptions and we will always see a variety of titles in analytical roles. It’s far more important for them to capture the needs of the role than to worry about the specific title. But, I digress…

For those who are frustrated, I would like to provide some assistance. I have seen approaches to analytics which begin with floating a business case to the executives in order to get “buy in.” To be honest, anyone can make almost anything look good in a PowerPoint presentation. And if you’re in a large company like I was a few years ago, it would have taken me a full year to cycle through all of those executives. It’s just not a practical approach and those who know me, know that I’m all about aiming for practical and realistic when it comes to analytics.

I’m more of a “prove it” kind of person, so business cases based on general information you obtained from the internet hold no value. Instead, I prefer the bottom-up approach of proving what can be done with analytics to show value. I would always seek out someone who was “feeling major pain” and would be open to accepting my offer of, “Do you mind if we give analytics a try in this application?” Those “feeling major pain” are more apt to try new approaches.

As a second piece of advice, allow me to use HR for this example. You may have noticed that most large companies are structured such that HR Business Partners are aligned to business areas. They represent their business area to the HR team. As such, these are the people that need to be advocates of analytics in HR. However, until you educate them in the capabilities of analytics, they won’t be able to understand the value they can bring by suggesting HR analytics to their business area. By educated HRBPs, I’m not suggesting a mathematical education on analytics, but more of a non-mathematical introduction to show them what is possible. For anyone out there who has heard my talks at HR conferences, it is always non-mathematical. HRBPs don’t need to DO the mathematics. They just need to know WHAT you can DO with analytics. With this approach, HRBPs can become your advocates and you will struggle far less with your analytical reputation.

If you are not in HR, you can still think of your struggle within the same context. Who are the people feeling pain where you think analytics can help provide insight into one of their issues?

I’ll leave it to the reader to contemplate their own situation and approach.

Until next time,

Tracey.

Tracey Smith is an internationally recognized business author, speaker and analytics consultant. She is one of the most highly respected voices when it comes to business analytics and HR analytics. She is the author of multiple business books and hundreds of articles in a variety of publications. Tracey has worked with and advised organizations, both well-known and little-known, on how to use data analytics to impact the bottom line. If you would like to talk to Tracey about consulting work or speaking engagements, please visit www.numericalinsights.com  or contact Tracey Smith through LinkedIn.

Visit Tracey Smith’s Amazon Author Page

 

How to Generate Value… One Data Set at a Time

The world is full of data and massive amounts of new data are being created every day. With so much data, the challenge has become one of discerning which sets of data will provide value. The answer to this question may be unique for every company and organization. Remember, it’s not the data itself that will provide value; it’s what you do with it.

I have been speaking and keynoting at conferences and corporate events for quite a few years and one of my most frequently quoted statements is as follows:

“The key to extracting value from analytics is a combination of focus and prioritization.”

This is a very significant point driven by the fact that so many companies seem lost in a sea of data and don’t know where to start. I, and many of my expert colleagues, all advise that you focus on the business questions that need to be answered. What is the question and what is it worth to your company to actually answer it? With this approach, you obtain both focus and prioritization.

You may also find that putting certain data sets “at the fingertips” of your employees will increase the speed and quality of their decision making. In these cases, the application of data is not for a one-time study but rather for daily use.

For these applications, it is important to determine the data needed to enable better decision making. Is it economic cost indices needed by your Purchasing team? Is it workforce information needed by your Human Resources team? I have no doubt that there are dozens of job roles within each company today that can be improved by providing employees with quick and easy access to information. The initial investigation of this is a project that can be run in any functional area. All you need is someone to lead the project and conduct the investigation into what data will be useful.

The data you need may be something you can use to speed up a process, save money, avoid a cost, improve the quality of your product / service, or improve your customer experience. Regardless of the functional area, there’s bound to be data that, when put in the hands of the employees, allows them to do their jobs better. Why not take advantage of that? It’s time to pause, think, decide, focus and execute on this idea.

Putting the RIGHT data in front of your people to ENABLE better decision making is where you will generate better outcomes.

Ready to put data at the fingertips of your employees?

Until next time,

Tracey.

Tracey Smith is an internationally recognized business author, speaker and analytics consultant. She is one of the most highly respected voices when it comes to business analytics and HR analytics. She is the author of multiple business books and hundreds of articles in a variety of publications. Tracey has worked with and advised organizations, both well-known and little-known, on how to use data analytics to impact the bottom line. If you would like to talk to Tracey about consulting work or speaking engagements, please visit www.numericalinsights.com  or contact Tracey Smith through LinkedIn.

Visit Tracey Smith’s Amazon Author Page

 

SHRM and CIPD: Two Approaches to Determining HR’s Future State

Have you ever stopped to examine the methods by which HR organizations determined what the future skill sets of HR should be? As you read this article, pay close attention to the approach. Readers with strong business acumen will see my point quickly.

The SHRM Approach

In 2013, the Human Resources profession recognized its need to change. In a study funded by the Society of Human Resources (SHRM) and the National Academy of Human Resources (NAHR), twenty CHROs were interviewed about their current expectations of HR, their future expectations, their opinion of HR’s ability to meet these expectations and any gaps that exist. The result was the formation of project teams to define the challenges facing HR and to make recommendations of how HR would meet the needs of tomorrow.

In June 2014, a Future of HR Summit was held to identify “pivotal challenges for accelerating the profession’s progress.”[1] The teams identified five forces of change that are predicted to emerge and create pivotal disruptive change in society, business and work. The five forces cited were:

  1. Exponential pattern of technological change,
  2. Social and organizational reconfiguration,
  3. A truly connected world,
  4. All inclusive, more diverse talent market, and
  5. Human and machine collaboration.

In the interest of brevity, I won’t explain each one here. You can read more about them in the book, “The Best is Yet to Come,” or you can read the SHRM reports from this project.

Based on the information above, the SHRM team envisioned five new roles to support the future of HR. The following descriptions are listed as they are described in the Future of HR Summit notes.

  1. Organizational Engineer: is an expert on new ways of working. He / she would be a facilitator of virtual team effectiveness, a developer of all types of leadership, and an expert at talent transitions. He / she is an expert at organization principles such as agility, networks, power and trust.
  2. Virtual Culture Architect: is a culture expert, advocate and brand builder. He / she connects current and potential workers’ purpose to the organization’s mission and goals. He / she is adept at principles and values, norms, and beliefs, articulated through virtual and personal means.
  3. Global Talent Scout, Convener and Coach: Understands new talent platforms and optimizes the relationships between workers, work and the organization, using whatever platform is best (free agent, contractor, employee). He / she is a talent contract manager, talent platform manager and career / life coach.
  4. Data, Talent and Technology Integrator: An expert at manipulating big data, understanding and modelling trends, and knows how to code to adjust the algorithms, as well as design work to optimally combine technology, automation and human conditions.
  5. Social Policy and Community Activist: A social responsibility leader. He / she produces synergy between the social goals of the organization, such as economic returns, social purpose, ethics, sustainability and worker health. He / she influences beyond the organization, shaping policies, regulations and laws that support the new world of work through talented community engagement.

I won’t comment on these positions other than to say that they seem a bit theoretical and not very “concrete” in their definitions.

As part of the Future of HR study, team members engaged a sample of HR professionals to ascertain the extent to which they agreed with the future vision. They conducted 22 interviews with CEOs, Directors and Board members on their perceptions of HR today and what they feel is needed for the future. The interviewees represented some of the largest companies and “some of the best and most highly regarded HR leaders in the world.”[2]

The summaries of these interviews were provided in a CHRO report card. I won’t list it here since it’s irrelevant to the point of this article, but I will say that the report card emphasizes many of the themes that we’ve been discussing for the past several years, namely, that HR:

  • Needs to expand its skill beyond its current capabilities,
  • Needs to gain experience to obtain business acumen, and
  • Needs to connect its actions to executing business strategies.

And now, the point of the article…

An important thing to note about this approach to determining the future needs of HR is that the initial interviews were conducted with CHROs, so essentially, a team of HR professionals interviewed HR executives. Later on, they presented the results to CEOs and we are left with the impression that the CEOs were not impressed.

From a business point of view, this approach was backwards. Having come from the engineering world where our company developed products, you don’t ask your engineering team about what new products to build. You ask your customers. SHRM did not interview its customers first. It interviewed itself (HR) first. That doesn’t align with the concept of “outside-in” customer service. It is not surprising then that the feedback from HR’s customers, conducted later in the study, did not agree with HR’s view.

The CIPD Approach

The previous study was conducted by SHRM, an American organization. As a comparison, let’s check the approach of an HR organization in another region.

The Chartered Institute of Personnel and Development (CIPD), is the governing HR body in the United Kingdom. This organization released a report entitled, “HR Outlook, Leaders’ Views of our Profession.”[3] For this research, the CIPD surveyed 143 senior HR leaders and, more importantly, 152 leaders from outside of HR. As you can see, the participation in this study was much larger and they included the customer view from the beginning.

Irrelevant to this article, but if you are curious as to what the CIPD concluded, read the remaining text.

There are areas where the opinions of HR leaders and non-HR leaders align and there are areas which are certainly misaligned. Much like the internal study I once ran for a Fortune 500 company, HR views its contribution to the company to be more substantial than how non-HR leaders see it.

As the CIPD states,

Although there is general agreement about what the organization’s strategic priorities are, HR and other business leaders disagree about what HR should be focusing on to achieve them. Our findings suggest further examination is needed about why there is such a notable difference in views about the suitability of HR’s current people strategy to achieving the organization’s future goals.

Some areas of disconnect reflect HR’s core people remit, and therefore their unique contribution, but others signal the need for action. Achievement of some strategic priorities (that is, innovation and productivity) require HR to work in a systemic way across the organization in complement to the traditional alignment with specialist HR areas or best practice. HR needs to have a deeper understanding of the business to be able to develop and support new ways of working across the whole organization system.

As you can see, topics like business acumen, innovation, analytics and technology keep creeping into our conversations each time we try to assess the future requirements of HR.

One of the biggest misalignments identified in the CIPD study is that HR sees its contribution to the organization’s future priorities being much more than how non-HR leaders see it. In the survey, 72% of HR leaders agree that their current people strategy will help the organization achieve its future priorities. Only 26% of leaders outside of HR feel the same way.

Until next time,

Tracey.

Tracey Smith is an internationally recognized business author, speaker and analytics consultant. She is one of the most highly respected voices when it comes to business analytics and HR analytics. She is the author of multiple business books and hundreds of articles in a variety of publications. Tracey has worked with and advised organizations, both well-known and little-known, on how to use data analytics to impact the bottom line. If you would like to talk to Tracey about consulting work or speaking engagements, please visit www.numericalinsights.com  or contact Tracey Smith through LinkedIn.

Visit Tracey Smith’s Amazon Author Page

[1], [2] Boudreau, Ziskin, Rearick and Schmidt. Summary of the Future of HR Project Summit, May 2015.

[3] Cipd.co.uk, HR Outlook: Leaders’ Views of our Profession, Winter 2015-2016.

User Experience Test with Power BI

As an entrepreneur who makes a living in analytics, it is crucial for my company to keep up with the best tools on the market. One of the most important tool categories for my work is data visualization. My tool of choice for the last six years has been Tableau.

That said, for the past 18 months, I have been occasionally testing Microsoft Power BI. You may have seen them appear in the upper right quadrant of the last Gartner report. Backed by the budget size that Microsoft can offer, and pricing themselves below Tableau, I can see it being a matter of time before Power BI competes head-to-head with Tableau.

Gartner Report – February 2017

With a change in position on the Gartner report, I felt it was time to yet again head into Power BI to test the user experience and capabilities. Keep in mind that the axes on the Gartner report are “completeness of vision” and “ability to execute.” It doesn’t measure the existence of certain capabilities and the customer experience. My benchmark for testing is my experience with Tableau Desktop Pro, Tableau Online and Tableau Server.

My previous tests of Power BI have always left me feeling very restricted in capabilities. In these cases, I was testing Power BI “Services” which is the online service tool. As an additional note, they also offer a desktop version.

Microsoft Power BI Services (Online Tool)

Heading back into the online service version a few days ago, I had renewed hope of capabilities based on the Gartner report. The first thing I noticed in comparison to Tableau is that the service connections with Power BI offer more on the social side. For example, Power BI says it can connect to a MailChimp account (email campaigns) to create a dashboard for email campaign statistics. I thought I’d start there.

Selecting the connection for MailChimp in the Power BI service was easy. I selected my simplest MailChimp account with one list in it. The connection was a success and to Power BI’s credit, it created a default dashboard and report. In Tableau, I would need to build my first visualizations from scratch.

I continued to Test Number 2 which was to switch the credentials (ID / password) of MailChimp to my Numerical Insights account. That account houses several lists, is much larger and has more activity (subscribes, unsubscribes, email bounces etc.). I switched the credentials and… Power BI still showed me the MailChimp data, report and dashboard from Test Number 1. I tried again and… a connection error.

I submitted this error to the Microsoft Power BI community and the response that came back was that you have to delete everything you have (MailChimp data, report and dashboard) and start over again. Did that work? Yes. Was it a good user experience? No. Do I consider that a “solution?” Definitely not.

Microsoft Power BI Desktop

The second response from the community was to use the Power BI desktop version. The community claimed that switching the credentials of the MailChimp account (ID / password) was possible on the desktop tool and that the desktop tool had greater capabilities. So, I headed in that direction.

About a year ago, I installed Power BI desktop on a Windows 7 laptop without any issues. I could easily connect to data and create basic dashboards. I could share dashboards with other people, as long as they didn’t have an email address which was designated as personal. The frustration here was that I couldn’t share a dashboard example with a small client who used companyname@outlook.com as her official business email. I did have to laugh a bit since locking out outlook.com is Microsoft locking out one of its own domains.

Today’s test was on a new Windows 10 laptop. I downloaded the desktop version and the installation produced no errors. However, launching the program was an entirely different story. A box opens, saying “Initializing model” and then I am left with a black box with some indecipherable text in the upper-right corner. At this point, the program is frozen and must be closed within the task manager.

The response from the Power BI community? It mentioned changing settings of GPU rendering within Internet Explorer (for some reason the program pulls its settings from this obsolete browser), stopping Nahimic for MSI if you’re running an MSI laptop (say what?), and installing the 32 bit version instead of the 64 bit.

I tried the first and third suggestions and managed to get a box to appear which allowed me to sign into my Power BI account. Sadly, it returned me to the same black screen. Clicking in the “blackness” at other locations revealed another menu. Sadly, I have to guess on this black screen where the menus might be. Clearly I have some sort of display issue.

I decided to attack this problem with the process of elimination. I am running two screens: one on my laptop and another with an external display. Each has a different screen resolution. Sure enough, if I disconnected the external display and then launched Power BI, it displayed correctly. So, the key to making Power BI work for me, is to unplug my monitor, launch Power BI and then plug my monitor back in. I suppose that with two different screen resolutions, some of my pain is self-inflicted, but surely I’m not the only customer with this set-up.

At this point, I headed back to my MailChimp test to run the same test that I had tried online. In the desktop version, a MailChimp connection is clearly labeled (beta). If I’d seen that label in the online version, I would have been more forgiving in my assessment of that tool.

I managed to connect to my simplest MailChimp tool. In the online version, I was spoiled by being handed a dashboard of my MailChimp information already made. In the desktop version, this doesn’t happen. No problem there since building visualizations from scratch is what I’m used to.

I headed into the test of changing the MailChimp credentials, i.e., changing the ID and password over to my more complicated MailChimp account. If you recall, the reason I decided to install the desktop version was to get around a lack of functionality in the online version.

I found where to change these credentials pretty easily and asked Power BI Desktop to refresh my data view. Unlike the online version, the desktop version was successful in this task. I could see a 5 year history of all of my email campaigns.

At this point, I had used up my allotted testing time. I have seen enough that I know that the online version is not something I would recommend to my clients. As for the desktop version, I do plan to continue testing and will track the results against Tableau.

I am convinced that Power BI will morph into something impressive, but I’ll need to give it more time. I promise to conduct more testing in the future now that I have resolved my desktop installation display issue.

Until next time,

Tracey.

Tracey Smith is an internationally recognized business author, speaker and analytics consultant. She is one of the most highly respected voices when it comes to business analytics and HR analytics. She is the author of multiple business books and hundreds of articles in a variety of publications. Tracey has worked with and advised organizations, both well-known and little-known, on how to use data analytics to impact the bottom line. If you would like to talk to Tracey about consulting work or speaking engagements, please visit www.numericalinsights.com or contact Tracey Smith through LinkedIn.

Visit Tracey Smith’s Amazon Author Page

Selecting Metrics and KPIs

By Tracey Smith
President, Numerical Insights LLC

As companies embrace the use of data for different purposes, sometimes it’s best to spend time determining or reviewing fundamentals like KPIs (Key Performance Indicators). Whether it’s measuring the success of HR, the success of supply chain, the success of your small retail store, the success of manufacturing or the success of one project, selecting the right KPIs is crucial.

KPIs are metrics that measure how well something is performing relative to its defined goals and objectives. That “something” can be as small as an individual and as large as the entire company. Correctly selected metrics and KPIs provide the ability to focus on what matters for success and business value.

Throughout 25+ years of analytics, I’ve taken a methodical approach to selecting metrics to ensure alignment with goals and business objectives. Admittedly, this takes time and effort, but without aligning metrics to business goals, how do you know when you are successful in your initiatives and how do you recognize problems? How do you keep your team aligned to your business objectives if the metrics you selected steer employees in another direction, or worse yet, in multiple directions.

Now, I have to say that one thing my customers really like about me is that I’m very practical. As with most things in the business world, there’s a difference between what you can do “in theory” and what you can do in the real world. Selecting metrics comes with several practical challenges. Here are just a few considerations:

  • How many metrics make sense for us to follow? How many is too many?
  • Is it worth the effort to produce every metric we would like to measure?
  • What compromises will we have to make due to limitations of our data systems?
  • What compromises will we have to make due to limitations with our chosen technology?

Most people struggle to select metrics and the end result is a huge report of… just about everything! Add to that the fact that KPI software vendors want to sell you a package with hundreds of metrics because that’s the only way they can charge you enough to justify their cost. Employees can’t focus on hundreds of metrics and too many metrics will confuse the message of “in which direction should we go?” The more metrics you have, the more likely they are to start contradicting each other in direction.

A focused set of metrics is worth its weight in gold. Just as we speak in analytics of aligning our projects to the “business questions we are trying to answer,” the same concept holds true with metrics. Begin with the business questions aligned to your strategic initiatives. Consider metrics aligned to measuring the success of those initiatives.

Until next time,

Tracey.

Tracey Smith is an internationally recognized business author, speaker and analytics consultant. She is one of the most highly respected voices when it comes to business analytics and HR analytics. She is the author of multiple business books and hundreds of articles in a variety of publications. Tracey has worked with and advised organizations, both well-known and little-known, on how to use data analytics to impact the bottom line. If you would like to talk to Tracey about consulting work or speaking engagements, please visit www.numericalinsights.com or contact Tracey Smith through LinkedIn .

Visit Tracey Smith’s Amazon Author Page

Critical Business Decisions, Quickly

By Tracey Smith
President, Numerical Insights LLC

We live in a crazy world where time is money and the faster you can make key business decisions, the more likely your business will still be here 10 years from now. Perhaps you’ve read this statement by Richard Foster of Yale University.

“The average lifespan of a company listed in the S&P 500 has decreased from 57 years in the 1920s to 15 years today.”

The radical change in lifespan on the S&P 500 has a lot to do with today’s increased pace of change and a company’s ability to react and / or be proactive in its decision-making. You may have also noticed a flood of companies actively assessing how to analyze their data to make good use of it, and in some cases, monetize its value.

Now, the story goes well beyond large companies and heads into smaller companies. In fact, smaller companies often have the ability to move faster than an S&P entity just by way of having to head through far fewer “approvers” before a decision can be executed.

Businesses of all types and sizes are now finding ways to deliver better business outcomes like increased revenue, lower costs, better quality and increased profit. Today, the need to gain insight into decisions affecting these outcomes is crucial for everyone. 

With today’s analytical tools, using business analytics to “see into” one’s business, is no longer out of reach from a budget standpoint. The battle in the business intelligence world is so fierce today that prices have become reasonable and tools are more accessible.

As one example, we’ve put an incredibly simple dashboard online for everyone to see. Click here to view it. We’ve greatly reduced the number of parts in this example since the real world application has over 10,000 parts to look at!

Even an example as simple as this one allows a company to make key decisions. If you didn’t click the link, it’s a look into a company’s product profitability where we can easily visualize which products contribute to the company’s bottom line, and which may need to be considered for deletion. Additionally, we can see that products that bring in the most revenue, don’t always bring in the most profit. Further, the company’s marketing department can use this information to target their marketing budget in the direction of increasing volumes sold on higher profit part numbers. This is just one of hundreds of examples we can present for valuable decision making.

The benefits of analytics are well documented:

  • Greater visibility and capability to analyze data and make important decisions with it,
  • Ability to measure detailed performance or products, services, warranty, customer service… almost anything you can imagine,
  • Company-wide access for employees and leaders to use information interactively and see data the way they need to see it for their own job, and
  • Ability to increase business results.

Insights lead to better decisions, which leads to better business outcomes.

Does this sound like something you’d like to hear more about? Use the registration link below and we’ll send you a free case study paper describing the business outcomes that can be obtained by looking at this information.

Register here to receive a Case Study paper. Available to new registrants.

Until next time,

Tracey.

Numerical Insights is passionate about using data to solve business problems. We have helped both well-known and little-known companies in multiple countries use data to make decisions which impact the bottom line.

You can find Tracey  Smith on the web at:
Numerical Insights Web Site
Find Tracey on LinkedIn
Twitter ID: @ninsights

Improve the Bottom Line with Complaints


by Tracey Smith
President, Numerical Insights LLC

For many businesses, the product they offer is offered by many others, or at least something similar. When it’s difficult for customers to distinguish and choose between the benefits of your product and the product of your competitors, it becomes a price war which erodes your profit margin.

How then, do you distinguish yourself from your competition?

The only factors left on which you can differentiate are customer service, quality and delivery. Today, let’s focus on customer service. All things being equal, your customer is going to select the company with the best customer service, so how do you ensure yours is the best?

Use analytics to examine your customer complaint data!

If you’re a large company, you probably have a centralized call center with more data than you know what to do with. Your issue will be determining where to focus your analytical efforts.

But that’s not the case for 90% of companies. Let’s assume you’re a medium-sized business or division with a customer service team of three to eight people. Consider the customer experience when they call.

  1. Did the customer get through or were they placed in a hold queue?
  2. If they went into a hold queue, how long was their wait? Did they wait or did they give up? Did you just lose this sale because you didn’t answer the phone but your competitor did?
  3. When they get through, are they placing an order or making a complaint?

Companies have a habit of focusing on the good from these calls and deem a call successful if the customer placed an order. But it’s an examination of the complaints received that will provide insights to improve your top line.

Customers may complain that:

  1. It took 10 calls to get through.
  2. Your product is defective.
  3. Your delivery is too slow.
  4. You sent the wrong product / you shipped a partial order.

Each of these cost you valuable cash.

  1. After several attempts and not getting through, the customers buys from someone else.
  2. Defective products must be returned for analysis and replaced.
  3. Slow delivery can become a return or lost sale when someone else can deliver the product quickly. (Amazon and Adidas have discovered that their return rates go down when they ship faster.)

How do you gain an advantage through complaints analytics?

Analyzing the quantity of complaints, the frequency of when they happen, the severity of their impact to the bottom line, product delivery times compared to return rates and other aspects of customer service will provide insights on which to focus for improvement.

Envision now, a customer complaint dashboard, visible to all employees which provides transparency, accountability to providing premium service and a focus on items which impact your top and bottom lines.

Until next time,

Tracey.

Tracey is passionate about using data to solve business problems. She has helped both well-known and little-known companies in multiple countries use data to make decisions which impact the bottom line.

You can find Tracey on the web at:
Numerical Insights Web Site
Find Tracey on LinkedIn
Twitter ID: @ninsights

 

86% of Executives Can’t Find Value in Analytics – Why not?

By Tracey Smith,
Numerical Insights LLC
www.numericalinsights.com
USA

In April 2016, a McKinsey survey revealed that,

86 percent of executives say their organizations have been at best only somewhat effective at meeting the primary objective of their data and analytics programs, including more than one-quarter who say they’ve been ineffective.

To be clear, we’re speaking of all analytics programs and not just those in any one functional area. So what went wrong? According to the McKinsey survey, the number one reason put forth by leaders is the need to design a structure to support analytics. Here are a few thoughts on their organizational comment.

When people come to me and ask advice about taking on a new leadership role in analytics, I always tell them to look at the org structure carefully. To whom does analytics report? Is the analytics team further down the org chart or much higher up? The higher up it resides, the more serious the company likely is about using analytics for decision-making.

When the function resides higher up, the leader of the analytics team has enough exposure and access to executives who have the “pull” to move projects forward. Gaining leadership support and the support of employees below these executives who likely need to reside on some of your projects, is much easier.

That said, you can still fail under this high-level structure in many ways. These failure modes exist regardless of where analytics reports. Here are a few:

  • You have no prioritization system based on business value. Your analytics team selects projects based on the “analytics fun” they will get out of them rather than business value. “Value” needs to be assessed outside of the analytics team whereas the analytics team members are the ones who are best suited to assess the “effort” required.
  • You have no formal document describing your data and systems. You find yourself under the weight of constantly supporting users who keep asking about definitions. Does headcount include interns? Expats? How was annual turnover calculated?
  • About 51 more reasons (for a nice prime total of 53) that I won’t make you read because it doesn’t matter to the point I’m making in this article…

If the analytics function resides further down, failure is not inevitable but it is more probable. However, I highly recommend putting an analytics leader in place who has a thick skin and is an absolute go-getter who deems failure to never be an option! This person will have to fight for the support he / she needs in order to move projects forward. This leader will need to lead by example and prove the value of analytics in order to get that support. By proof, I don’t mean a “pie in the sky” PowerPoint deck about the theoretical benefits of analytics that anyone can drum up off the internet. I mean hard-core proof of analytical benefits using the company’s own data. Yes, that takes effort but we have our “go-getter / failure is not an option” leader, right?

This leader will need to “get out into the business” and speak to more layers of the organization than the analytics leader who reports higher up. This leader will need to “rally the troops” even if those troops are purely volunteers. It can be done.

Regardless of the levels, one main failure mode remains the most common one I see…

There is no plan; there is no strategy.

The analytics being conducted is “whatever lands on our desks.” The team is in firefighting mode with no time to plan. This isn’t true for all analytics teams, but it does seem common enough to mention.

Without a plan, some teams get caught in the very long duration of “trying to get ALL of our data in one place” or trying to be like Walmart and Amazon. Value will pass you by.

If you put a strategy in place, it’s quite the opposite approach. We are not concerned about ALL data. For 99% of companies, we are not trying to be Walmart or Amazon. We are concerned with defining what we need to know and concerned only with the data associated with that. I have said many times that “success in analytics is about focus and prioritization.” This is similar to what Bernard Marr said in one of his books ( Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance ) , namely:

In order to reap the benefits of Big Data you don’t have to collect everything and produce the biggest, most complex database in the world. As I’ll explain in this chapter your aim is actually the opposite – to get really clear about what data you need, what data you can and will use and build the smallest, most straightforward database in the world!

So, if you feel like you’re drowning in your analytics approach, it’s time to take a step back and think about what’s really important. Only then will you get the focus and prioritization you need.

Until next time,

Tracey.

Tracey is passionate about using data to solve business problems… all types of business problems. Specializing in multiple areas of business analytics, Tracey has helped well-known companies in the U.S., Canada, the UK and Europe use data to make decisions which impact the bottom line.

You can find Tracey on the web at:
Numerical Insights Web Site
Find Tracey on LinkedIn
Twitter ID: @ninsights
Interesting Books to Read
Research subscription

DOES A 50/50 GENDER RATIO TARGET, AS ANNOUNCED BY BHP BILLITON, MAKE BUSINESS SENSE?

AN HR-ANALYTICS PERSPECTIVE

by Gido van Puijenbroek,
Managing Director, AnalitiQs B.V.
Amsterdam

Gido van Puijenbroek is based in the Netherlands. When asked which books he would recommend to readers, Gido recommended  Show Me the Numbers by Stephen Few for English readers as “must-read” since visualizing insights is critical to be successful with analytics. For Dutch readers, he recommended “HR-analytics: Waarde creëren met datagedreven HR-beleid” by Irma Doze and Toine Al as a practical guide to HR Analytics.

BHP Billiton recently announced they aim for a 50% female workforce by 2025. This target is one of the boldest gender targets any global company has set, especially since mining is often regarded as a men’s world. The driver behind this decision is value creation. The miner says that a better gender balance in the workplace will improve performance and ultimately improve shareholder value.

When I read this news, as a Data & Analytics professional, a number of questions immediately popped up in my mind. Let me share the four most relevant ones. Does diversity indeed improve performance? Should there be a 50/50 ratio, or could a similar performance impact be achieved at a different ratio? Is this ambition realistic? Will this decision indeed create shareholder value? Let’s have a closer look at these questions. Can they already be answered and/or how could HR Analytics help in answering them?

Does diversity indeed improve performance?

As it turns out, a tremendous amount of research on the topic has already been conducted. For instance this recent study by McKinsey, a meta-analysis from the Haas School of Business, this study from the Harvard Kennedy School, and an HR-analytics project by Shell (Esther Bongenaar and Linda van Leeuwen) very recently.

From a quick scan of the articles it seems that companies that focus on Diversity and Inclusion (the two often come together) perform better when there is simultaneous attention for things like inclusive behaviour, inclusive team leadership, the absence of strong sub-groups and training for group-process skills.

For BHP the conclusions of their analytics seem to be in line with the conclusion above. “BHP Billiton’s 2013 Employee Perception Survey showed that increased inclusion correlated with increased performance”. In addition, Andrew Mackenzie, BHP Billiton’s CEO, indicated that at the company’s “most inclusive and diverse sites” performance is 15% higher.

All in all, I think we can say that diversity and inclusion can indeed impact performance if it is embedded in a broader context. Companies should investigate and measure wether they have created the right circumstances.

Should there be a 50/50 ratio, or could a similar impact be achieved at a different ratio as well?

Under the supervision of Rohini Anand, Sodexo performed their own HR-analytics project, which  focused on, among other things, this question. Although this analytics project is just one observation, the case offers a good starting point for an answer to the above-mentioned question. According to the study the male/female ratio should be between 40% and 60%. “Teams that fit within this gender balance zone generate, on average, results that are more sustained and predictable than those of teams with less than 40% or more than 60% of either gender”. For instance, gender-balanced teams achieved on average, a 12% increase in client retention; positive organic growth, growth profit and operating profit over three consecutive years. If BHP implemented the Diversity policy purely to boost company performance, it might be better to aim for a 40/60 ratio as that would be easier to achieve than a 50/50 ratio. However, if corporate citizenship is also a driver, then 50/50 might be the right target.

Is the ambition realistic?

It is hard to find input for this question, probably because the answer to this question very strongly depends on company context. For example, some industries attract fewer women and in some regions, access to education and the labour market is less straightforward for women than in other regions. Even BHP indicated they don’t really know if their ambition is realistic – they speak of an aspirational goal and indicate it will be a challenging change.

However, research in combination with analytics can provide an answer to this question. As a first step, BHP could identify the skill sets that they are looking for, and they can also formulate skills that are similar / substitutes. Next, they could scrape the Internet, or buy labour market data, to build a labour market demand and supply picture for these skills. This would give them insight in the total labour pool and the share of candidates that they are looking to recruit. Moreover, they can conduct research amongst the people in the supply base to assess company attractiveness, predict the willingness of people to relocate to other BHP locations and identify the factors that influence joining decisions (e.g. pay and development opportunities). These insights will help to calibrate and influence the supply picture. Once demand and supply have been modelled, BHP can get an idea of whether their ambition is achievable.

Will the decision create value?

Under question 1, I set out that by focusing on diversity and inclusion companies are likely to enhance performance, as long as they properly embed the concepts in the business operation. To answer this last question about value creation, it is vital to understand how much it will cost to create the more diverse and inclusive teams. Because in financial terms, value is: revenue minus costs.

To get a better understanding of the costs, BHP could look at the historical data of their more diverse teams, and investigate which costs emerged when these more diverse teams were created. One could for instance think of answering the following questions: are sourcing costs different when a more diverse pool of candidates has to be identified; do attraction costs change because we have to build a segmented labour market brand, because we may have to tap into new candidate pools and/or we may have to bring people in from further afield; do investments in retention change to keep women aboard; how much investment in training is required to establish the right behaviour, which impacts the value that can be created by focusing on diversity?

If the performance increase is higher than the total of investments made to become more diverse, then the decision will indeed create shareholder value and would probably be the right one.

 

An idea for HR: Let’s look at data instead of numbers.

By Sergio Garcia Mora
Bachelor in Labour Relations and Data Mining Student

Sergio Garcia Mora is based in Argentina. For English readers, Segio recommends the book, The ROI of Human Capital by Dr. Jac. He also recommends Argentinean author Luis Maria Cravino’s book called “Medir lo importante” (Measuring the Important) and Jose Maria Saracho’s book called “Talento Organizacional”.

You can view the original article in Spanish here.

When I started my Career on Labour Relations at the University, and I asked my classmates why they chose this career, most of them replied “because we don’t have to deal with math and numbers”, and suffering two statistics courses along the career didn’t seem so distressing.

Thinking about this situation, one of the reasons I think this happens to people who chose “soft” careers (namely HR, Psychology) is because we hit a wall thinking how hard it is to solve an equation instead of thinking of what can I do with the information the equation provides? It might be a subtle difference, but once you know that certain “maths” may help you find answers to specific issues, the negative energy that blocked your way transforms and allows knowledge to flow.

This way of thinking doesn’t exclusively belong to HR. Last year, when I started a postgraduate course in Data Mining, every single one of my classmates asked me “Can you use Data Mining in Human Resources?” and my answer was “Of course you can!” This prejudice is established because we (HR functions) are not perceived as a data-driven area (despite that we own our employees’ information when they work in our company).

“They don’t give HR a place at the Decision Table”

How are “they” giving HR a seat at the Decision Table if we don’t speak the corporate language? And the corporate language is results. If we are not able to show our own results, how do we gain a decision-maker’s trust?

And thinking of results, it’s not necessarily just saving cost and time. We can go beyond. Looking how our HR information relates with other company data, we’ll have the opportunity to drive our efforts.

Not long ago, asking Daniel Yankelevich, a key Data Mining player in Argentina (and a person I love to listen to whenever I can), what makes a miner good, he replied with 3 things:

  1. Must know the company’s business.
  2. Programming skills.
  3. Must be able to turn conclusions into actions.

Ok, perhaps programming might be discouraging to HR professionals, but:

  • Can we have business acumen? It’s a must.
  • Can we team up with other areas to conduct the analysis? It’s a good idea.
  • Can we drive conclusions into action? Yes, we can.

My suggestion is simple. Don’t get messy with math, Let’s look for relationships among data, for instance:

  • Is there any relation between our communication/training/compensation actions and   the quality of the company’s product?
  • What profiles show more turnover?
  • What are the characteristics of the frequently absent workers?
  • What do top performers have in common?

When we set out to focus on what we want to achieve, “playing” with data is much simpler. There are techniques that allow us to look for relationships between variables that don’t seem to be connected, but even without getting to that sophistication level, there’s a lot of available information to match, contrast with, that we haven’t taken advantage of yet.

People make the difference

Nowadays, many companies have a phrase like people are the most valuable asset in their Mission and Vision. So, how can we measure people’s impact on company’s results? By looking for patterns in data. Not only in HR information but finance, production, sales, safety, etc. If we, the people, generate value in every company, it’s necessary that we find ways of showing the value that we produce, and how our decisions affect business’ results.

I confess that when I was deciding what career to choose, one of the most important factors was being able to work with people and not with numbers. But when I started to dig into HR data I found curious things, like I didn’t have absenteeism issues with millennials but I did with 35-40 year-old people, and millennials showed a lower turnover than X-Generation professionals. With this data I’m able to:

  • Discuss ideas and preconceived concepts.
  • Make better decisions.

“Working with numbers” is not taking the human aspect away from the Human Resources job. On the contrary, it allows us to be precisely “more human” by providing more accurate feedback, or replying to a complaint with more precise information than vague answers or with inconsistent answers waiting for people to get tired of arguing.

This way of thinking provided me with a whole different perspective of my career. Being able to relate data with business results allows me to separate apples from oranges, evaluate our “best practices” in order to keep the ones that bring better results, letting me save money, time and be more efficient.

That’s why I say, let’s forget about numbers and math, and start focusing on data and its relationships. That’s a great way to become a strategic partner, and gain a seat at the Decision Table.