Finding Meaningful Ways to Use HR Data

One of the biggest challenges people have with using more data in their talent management process is that many leaders just don’t know where to start. Most HR organizations have tons of data on end to end talent management from recruitment to training to operations, but it is not easy to see meaningful patterns within all the data.

HR data used to be something easily captured in spreadsheets. Some of us have evolved to using more robust applicant tracking systems and talent management tools. Cutting edge HR teams are able to use the Big Data in their business to fuel a mature analytics engine that leads to insightful reports and business dashboards. Recent leaps in technology have given data hungry HR professionals access to a wide range of employee information that can be used in ways unimaginable just a few years ago.

To really find meaningful ways to use HR Data, today’s HR professionals needs to have at least a working knowledge of the data they have in their business. To be successful they need to know how to access and analyze the data, provide it to decision-makers and incorporate the data into a living process of continuous improvement.

In the end, success with HR data all boils down to the culture of the business. Is the team, or at least a number of the team, tech savvy and analytical? Is curiosity encouraged when it comes to finding new data? Is proactively mitigating risks and eliminating waste in the talent management process encouraged? If yes, then you are doing better than most.

Finding meaningful ways to use HR Data is not just about the cool new technologies available, nor is it just about harnessing the power of Big Data. It is as much as, if not more important that the HR team share a culture that optimizes the use of HR Data in defining strategy, making decisions and improving the business.

If you are wondering how to find more meaningful ways to use your HR Data, connect with me. I have helped dozen of HR teams to find ways to up their game when it comes to growing a data-driven culture that can maximize the big data in their business.

HR & Recruitment Analytics – The recruitment and retention of top talent is the biggest challenge facing just about every organization. DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

Whats Missing in Your Cost Per Hire Metric?

One of the most common metrics used in recruitment is cost per hire. Generally used to bring together all the costs associated with filling an open position, cost per hire is probably the most widely used metrics across all types of recruitment. It is a close to a universal metric as we have. However, most of us are not using it correctly.

First make sure your calculation includes all factors related to filling the positon that have an external cost like marketing, advertising, job fairs, job board fees, travel time to events, remote interviewing, etc. Any and everything you can think of that happens outside the office that adds to your total cost.

Now do the same for factors that are internal to the business. Salaries, bonuses, reimbursement expenses, application tracking systems, copy and printing costs, etc. Make a list and notate the expense for any and everything you can think of that happens inside the office.

In both cases, also include data for shared costs from expenses that cover more then one opening. In many cases we don’t include things like rental expenses, association fees, government requirements, really anything that your organization spends money on that directly supports your recruitment efforts. In many cases, you can divide the total amount by open positions to come up with some kind of weighted amount assigned to each open req.

Now one more piece to your cost per hire metric, that most of us miss. Expenses related to not filling the position. How much is lost in productivity? What revenue forecasts come up short? How much is spent on overtime and other compensation for staff covering for the open position? When you factor these items in you can get a much deeper understanding of the cost per hire to the business.

If you are doing all of these things and feel you have a very solid cost per hire metric, then you are in the minority. In an ideal world, recruitment teams can better allocate resources based on what positions cost the most to fill. Better understanding all the data points that are added into the cost per hire calculation can also uncover opportunities for savings that you might not otherwise see.

On the other hand, if you are looking for some guidance on assessing your cost per hire metric to make sure its optimized to capture all of the relevant data points to your business then connect with me. I can help you get a true read on the cost per hire in your business.

Quick Analytics Survey: Reasons Why Analytics Projects Fail

I am in the process of sending out a quick analytics survey to my LinkedIn connections asking what is the most common reason analytics projects fail.

The survey will be extremely helpful as I am preparing a new book that focuses on why analytics projects fail. I want to list out the most common reasons and then add what can be done by analysts to prevent these causes of failure.

Here are the reasons I have come across in my career as an analyst and consultant.

Reasons Why Analytics Projects Fail:
#1 – Lack of Focus, no one makes the project a priority.
#2 – Lack of Vision, no clear idea of what the end product looks like.
#3 – Lack of Management Support, no support from above.
#4 – Lack of a Champion, no one to cheer team on to completion.
#5– Organizational Politics, gets killed by someone else.
#6 – Lack of Funding, not enough money to complete the project.
#7 – Lack of Talent, don’t have the experts need to be successful.
#8– Lack of Resources, not given all the tools you need to finish.
#9– Bad Data, you complete the project, but end up with bad data.
#10 – Key People Leave, someone leaves that can’t be replaced.
#11 – No End User Participation, not useful to those its built for.
#12 – New Technology, it becomes obsolete before it can be used.
#13– Over Reliance on External Help, slowed by waiting for others.

4.6

If you have a reason, not covered by this list, please feel free to reply with that’s as well.

This future book will be a companion book to my recently completed Analytics Guidebook and my current book in process entitled Data-Driven Cultures.

If you are having problems in your organization with analytics projects faltering or failing to be the success you had hoped for, let me know. I can help you identify the cause, come up with a solution and help you ensure your analytics projects becomes a huge success to the organization.

Only Data Dinosaurs Promise “One Day” or “On the Spot” Hiring

In the ever quickening world of BPO companies in the Philippines, the latest recruitment slogans promise One Day or On the Spot Hiring. I even saw one today that promised a coaching session on how to pass the interview before the interview. Crazy. Like the last dinosaurs, these big companies are making a futile effort to avoid extinction.

Anyone ever involved in recruitment will tell you, that its hard enough to find good candidates, but trying to find rock stars with a one day, end to end, recruitment process is ludicrous. Not using more data and analytics in their process, will lead them to walk with the dinosaurs.

When it comes to trying to compress the recruitment process cutting edge companies look to technology and data analysis to help them narrow the field and make quicker hires. While dinosaurs just through more manpower at the problem. They ramp up with staffing staff and take shortcuts in skills assessment, candidate fit and potential success to meet the ever increasing demand for talent.

When you see the headlines promising one day hires, you look at the companies and see they are doing things like its still the Jurassic Era. Resume screening in mass, scaled down skills tests and group final interviews. No demographic profiling, no analysis of the candidates distance to work or difficulty of commute, no predictive modeling based on candidate data to show likelihood of employee success. Its like watching a bad sci-fi movie about dinosaurs taking over the planet. It will not end well.

In today’s hyper competitive job market, only the companies who evolve to using more intelligent recruitment methods will prevail. The rest will someday take their place in a museum of failed BPO companies from the early 21st century.

And its not that expensive, not is it really that hard to invest in analytics solutions. The cost of ramping up and hiring more people to do hiring is always more costly over time then a good business intelligence tool.

Instead of shortening your process to stave off eventual extinction, evolve your business to get with the times. Don’t end up like everyone else offering the promise of expedient hiring to fill seats, that in the end just need to be filled again and again. Hire a recruitment analytics expert, have them dig into your data and come up with a smarter solution.

I can show you how. I have helped dozens of BPO companies come up with analytics solutions that help them avoid the trap of one day hiring. Connect with me if you want to survive.

Change Has Come > I am DMAI

About 4 years ago I attended a conference on Business Process Outsourcing where the keynote speaker was former President Aquino.

When he entered the room, I was sitting on the edge of the middle row and as he walked to the stage he walked right by me. I’m not much for being impressed by that kind of thing, but in this case it was pretty cool. I mean how often does someone get to be a few feet away from a president of any country.

In the four years since my brush with political celebrity, I am looking forward to getting another chance to be in the same room with a president. On August 17th, I will speaking at this event where current President Duterte will be giving the opening speech.

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So from being in the audience 4 years ago, to now being on the same stage 4 years later. It is a very satisfying feeling to think how far I have come in 4 years. From a “fresh of the plane” foreigner with just a handful of connections to being one of the more in demand public speakers. All because I love analytics and have a passion for sharing my key essentials for data-driven decision-making with my beloved Philippines.

Change has come!

Living the dream!

#IamDMAI

Using Data Analytics to Assess Work Ethic

When you oversee the growth of a team from 6 to 100 employees in just over a year like I have, one of the biggest challenges you face is keeping up with recruitment requirements. When in rapid expansion mode, it is easy to lower standards and fall into a “just fill the seat” mentality. When this happens, high attrition generally follows.

One way to try and curb high attrition rates is to get better at measuring candidate work ethic. For most people assessing the work ethic of candidates is something that seems very subjective and not something that is east to apply metrics too. And in with that assumption, you are missing some very easy data points to capture and use in being more analytical in your recruitment process. Let me highlight three data points to capture in the recruitment process that have a strong correlation to work ethic.

Timeliness
Resume Quality
Preparation for Interview

We all make note of these items during the process, and often include them in the overall evaluation of the candidate. But rarely is anyone capturing these items as data and using it to help measure work ethic and use it to predict work ethic once employed.

Timeliness is simple. Where they early, on-time, late, really late or a no show for any of the interviews in the process. If people are early or on-time it’s a positive and can show a general behavior once employed. On the other hand if a pattern of being late or not showing up is already evident before being hired, why would you expect that to change once they are part of your team?

One thing that is common here in the Philippines is dramatic excuses for being late or missing interviews. If you are or ever have done recruiting here, I am sure you can rattle of a long list of excuses; family emergency, death of a loved one, getting sick, and stuck in traffic being the ones I hear the most. Its easy to dismiss the excuse as a valid reason to be late or not show, but time and time again when we hire people who started like this, they don’t stick around. Putting a weight behind timeliness is extremely important. Over time you can track the attendance patterns of people you hired with low timeliness scores and I guarantee you that you will see a strong correlation between the two.

Resume Quality is also something that generally has a direct reflection on the candidate’s level of professionalism. If you are expecting someone to treat your business with respect and hard work, yet their resume is out of date, incomplete and/or full of typos, once again you are fooling yourself. Im sure we all think at some point the resume is just a resume and bad candidates can have good resumes and vice versa. Well if you do think that, then don’t you owe it to yourself to start tracking data to validate that. When you find you are mistaken, and bad resumes general equal bad employees, you can thank me. Come up with simple scoring system. Like an English teacher would grade a paper. Grade the resume and add the data to both your decision-making and your data analysis.

One of the deal breakers for me when I interview is how prepared is the candidate. When I ask them how did the hear about the job, and they say a friend told me to apply I get concerned. My follow up being did you research the company before coming here. When they say I didn’t. Its pretty close to an automatic fail. If a friend told them about the job, but they didn’t do anything to learn about the company it’s a clear sign they are not taking this serious. So why would I expect them to take their job serious once they start. Again come up with a simple scoring system to indicate how did they hear about the job, what kind of research did they do about the company and how much knowledge do they come in with about the job they are applying for.

So there, you go. That’s how you can add some powerful analytics to your recruitment process. Come up with you own measurements for timeliness, resume quality and interview preparation. Use them along side the tests and assessments and interviews, to build a more complete candidate profile. All track these data points over time to compare to data once they are an employee like schedule adherence, productivity and quality of work. I promise you, you will see strong correlations between the pre hire and post hire data.

Key Analytics Essentials For HR Success

A few months back, I had the pleasure to be one of the resources speakers at the HR Congress. Put on my good friends at Ariva Events Management, the event was at the SMX Convention Center, Mall of Asia Complex, Pasay City, Philippines.

This HR Congress aimed to provide Industry Updates, Expert Insights, Good Practices and Experiences, and Practical Knowledge; generate thought-provoking and challenging discussions; and encourage professional networking and strategic partnership among stakeholders, if only to further the HR Agenda supportive of the organizational targets.

A primary goal was to cross-examine the major HR Trends quickly moving forward and impinging on the business in developing an effective ‘Employer of Choice’ branding. The Congress also shared how to develop employees to optimize their potentials; and build an emotionally-committed multi-generational team.

The Two-Day Event covered Six Essential Cores in People Management, each one with a tie into my favorite topic… analytics.

1. Strategic Human Resource Management (SHRM)
Overview of the business environment vis-à-vis the changing roles and functions of Human Resources in general. With so much data now available, its much easier for HR times to decide where to spend their time and focus. Without good HR analytics you might as well be fumbling around in the dark

2. Human Resources Information System (HRIS)
Overview of tools and appropriate support structures for administering HR-related information. This aims to impart knowledge and skills in managing information resources to support basic records management and people administration. A reality is that most of us are still using MS Excel to manage talent pipelines and HR data. So learning how to use more cutting edge technology is key to being successful in the Information Age.

3. Employee Selection
Methods of employee selection and concepts in forecasting and identifying competencies; an Interview Guide may be developed that will assist in spotting competencies to match people needs. There is so much competition out there right now. The supply is far outweighed when it comes to top talent. You need to turn lose your business data to help you attract, hire and retain while others deal with massive turnover and low employee engagement.

4. Performance and Rewards Management
Case studies and exercises, concepts in managing employee performance; pay and benefits Learners will be able to hone skills in performance planning, performance assessment, coaching and giving performance feedback. All this generates massive amounts of data that can be turned into valuable insights.

5. Employee Development
Skills in determining employee development needs; different training and development interventions; participants are expected to come up with an employee development plan. It is getting harder and harder to keep good people around. SO, you need to use your data and a good HR analytics solution to make sure you are giving your employees the exact opportunities they demand, before they jump ship.

6. Employee Relations and Well-Being
Equipping participants with the know-how in employee relations including basic labor laws and managing employee organizations. Employee well-being issues such as employee stress and burnout, smoking, and work-life balance will also be covered. This area is often very manual and rarely included in a good analytics solution. That doesn’t have to be the case.

SO, as you can see their in an analytics solution to just about any issue facing HR. In fact, the recruitment and retention of top talent is the biggest challenge facing just about every organization. DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

You can also reach out to my key business partner, Ariva Events Management to request an in-house training featuring me as your resource speaker.

What ever you do, make sure you optimize your use of data and analytics in your HR decision-making processes. If you don’t your organization will face a much more challenging path then ones who do.

Let Your Data Tell You When It’s Time To Say Goodbye – Habitual Tardiness

Came across this blog post the other day and it inspired me to write about how use analytics to know when to let go of troublesome employees.

The first type I’ll blog about is ones who are habitually tardy.

“Handling employees who are constantly tardy for work is one of the difficulties of being a manager — no matter the industry. Simply firing them isn’t always the best policy when you consider the effort spent trying to hire their replacement. On the other hand, if your organization thrives on teamwork, having one team member not pulling their weight is bad for office morale.” Wise words form the blog I read.

The best way to deal with tardy employees is to look at the various data points that are generated by their behavior. This allows you to be unbiased in your decision-making when it’s time to say goodbye. The 5 data points I suggest you focus on are:

Total Down Time. What % of their shift did they miss plus what time it takes for them to get ready to work (logging in, opening systems, etc.) plus any time out of production you use to counsel them. Take this number and compare it to someone who comes in early, is ready to go when the clock starts and you never have to pull out of production to give warnings too. You will see a surprising difference of how much less time habitually late employees are contributing for the same pay
Distance To Work. Look at how far they have to travel every day to get to the office. I am betting its further than most. There is generally a strong correlation between schedule adherence and distance to work. Not always, but a high % of the time.
Difficulty of Commute. Look at the commute they have every day. How much time do they spend in traffic? Do they have to switch transportation modes? Is their route full of unpredictable impediments? It’s likely that challenges in their commute also have something to do with their consistent tardiness.
Quality Scores. Again, as a general rule, employees who have trouble getting to work on time also have lower than average quality scores.
Primary Production Metrics. Likewise, you generally see lower production metrics from employees who don’t start their shift ready to go.

“When simply walking by their desk to acknowledge a late arrival doesn’t stop the issue, it is probably time for a one-on-one meeting with a frank discussion.” Use this one-on-one time to review these metrics. Share with the employee some insights into why they might be late so often as well as how it effects the business.

It’s my experience that when you show them the data, it generally has a much more profound impact then just talking about things in a general sense. The power of your total down time is the highest on the team. You have the longest and most challenging commute. Your QA scores and production metrics are in the bottom 25% of the entire team. All of these can either be more motivating to the employee or they can provide a good reality check.

“Being proactive as a manager while showing you understand and even relate to their personal situation might enhance that employee’s performance over the long haul. It is vital you take the steps to get to the bottom of the issue before contemplating further discipline.” Using these data points in your verbal, written and final warnings add much more weight to your counseling. And when/if they finally hit the 3^rd strike, you have a lot more data-based rationale behind your final decision. See the original article here:

How long until You Give Up on an Employee Who Keeps Showing Up Late?

If you need help in coming up with a way to build more analytics in your schedule adherence and discipline process, just let me know. I am happy to help.

Using Analytics To Validate A Candidates Primary Motivation For Work

I am often asked how to better use analytics in recruitment. Besides the fairly obvious ways like analyzing your pipeline for trends or looking at candidate demographics, I sometimes suggest coming up with a way to correlate candidate answers to items in their resume.

For example, what motivates the candidate to work. The question can be asked a number of ways. Here in the Philippines, it is pretty standard to ask a candidate why do they want to work. This is a different question then the more universal why did you apply for this job question.

The rationale for the question is generally to learn more about the candidate as it applies to commitment and work ethic. Common answers are I need to help meet my family’s financial needs, support my children, pay for a younger sibling’s education. The problem I with this question is that it set’s up a situation where the interviewer can feel sympathetic to the candidate.

As a counter to this, I train my team to look for a few queues in the resume to help validate the genuineness of the candidate’s answer. In short to do some analysis, and record some data for future analysis.

Most resumes here have a biodata section that includes things like parent’s occupation. This is a good place to probe more if the reply to the what is your primary motivation to work is family financial needs. You should also notate this and start compiling data on each candidate response that can then be used down the road in looking at their success as an employee if hired. You can also get a sense for what types of people are being attracted to apply for open jobs. Both can be very valuable insights when building some predictive analytics into candidate screening.

You can also look for employment gaps. If they are working to serve an overarching financial hardship, then there should not be significant gaps in their work experience and/or job hopping. This is a great insight into dependability and work ethic. Make sure to capture this data as well.

You can also ask them specifically how working will meet their primary motivation. Do they have specific costs and amounts at hand, or is the answer more general or even vague? Have they really thought through the cost versus their compensation? Probe to see if they have done analysis themselves on their own needs.

SO you get the idea, one simple questions with a short reply can actually lead you to much deeper analysis both during the interview and when looking at trending over time.

Ideally, every question you ask is something you can use to generate data. Every answer they give should be validated against the data in their application or resume. And here you create and capture more data.

In the end you will amass a wealth of information on candidates that you can analyze to look for patterns showing you who to hire and who not too. It can also help you determine that if you do hire them, what kind of employee will they become. Adding some simple analytics at the front end opens things up to a whole new level of data-driven decisions making in your talent acquisition process.

If you need a little help in adding or enhancing analytics in your recruitment process, let me know. Happy to help!

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

Looking for Unicorns – One Reason It Is So Hard To Find Good Analytics Talent

When I look at job requirements for analytics jobs I generally find myself thinking, is this person recruiting from the same talent pool the rest of us are? Or do they really believe that the narrowly focused and hyper specific skill set they are looking for don’t really exist.

Often I am asked by HR and Recruitment professionals here in the Philippines to help them figure out how to bring more analytics into their talent acquisition process. Before going to deep, I generally review job requirements to see how realistic the requirements are.

You would be surprised how often the people doing the hiring have no idea how hard it will be to find candidates, let alone if they even exist.

For example, a Data Analysts with an advanced degree in analytics, 5+ years related experience, with knowledge in a wide range of specific coding languages (SQL and R) and business intelligence applications (Tableau and IBM Cognos), and who also know how to perform advanced predictive modeling. And willing to work in an office (Eastwood in QC), that is hard to get to during commute hours for a total compensation package that is way below market rates (45,000 PHP).

That’s a real posting I just pulled off jobstreet.com

Good Luck with that.

Seriously, recruiters are often tasked to find analytics professionals that in reality are few and far between. There are no degree programs in analytics. You need to know what related course work will potentially make a good analyst like statistics or computer science. This broadens your talent pool when you know what schools have been producing graduates who have the foundation of analytics when they leave school.

Work experience is a tough one to gauge based on titles. I have seen far more “analysts” who are just doing basic reporting then I have true analysts with the ability to discover patterns in business data and turn them into actionable insights. You need to dig deeper to find out what data they were working with, what tools they used to analyze it and how they presented it to decision-makers.

Knowing certain coding languages is a plus, but given few businesses have the exact same data structures, it will take as much adaptability as experience to be successful in your job. Same with BI tools, just because you know how to refresh and share a business dashboard in Tableau doesn’t mean you know how to build a new one from scratch. Having experience is important as it lessens ramp up time. But don’t be fooled that it gaurantees success.

Analysts are in super high demand right now. Getting them to work like a traditional office worker lessens their ability to optimize your business. They need space to be curious, autonomy to discover and flexibility to put energy into projects that make a significant difference. 9 to 5 office hours, chained to a desk, following all the controls in place for a traditional office staff member is a waste of a beautiful mind.

And when it comes to pay. Six figures is not as farfetched as it might sound. If you are able to do a real cost analysis of what the analyst will save the company and/or new revenue they can help generate, they really are priceless.

SO before posting that job requirement, do a little analytic yourself to make sure you are not hunting for a unicorn.

Let me know if you need helping recruiting analytics talent. I can help you attract their attention and assure they will be successful once you get them.

General Analytics – Analytics is the application of using data and analysis to discover patterns in data. DMAIPH specializes in empowering and enabling leaders, managers, professionals and students with a mastery of analytics fundamentals.

To this end we have parterned with Ariva Events Management/Ariva Academy to offer a wide range of analytics themed trainings across the Philippines. Our next learning event will be on March 31 in Ortigas. It is called Data-Driven Decision-Making for Owners, Managers and Leaders. Click here to find out more >>>

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out what we can do to help you acquire the analytics mastery you and your organization need to be successful in today’s data-driven global marketplace.

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