Five Year Plans – What Analytics Do You Use?

As the 5th year of my original business plan comes to a close, it seems like a good time to reflect on how things have played out.

There are plenty of data points to look at to determine how sound my original plan was and if the course changes made along the way proved to be the right ones to take.

The single most important metrics in my 2012 business plan where # of Filipinos trained to be analysts, # of schools I have worked with and $ of revenue I have generated.

Looking first at the revenue, because if you cant make a profit after 5 years then you are doing something seriously wrong. I started making a profit I year 3, which is pretty typical of business startups.

I made my most money in year 4, but had a more diversified revenue stream in year 5. Revenues have been closer to my actual target as year 4 was one of almost too much growth.

Originally just making money from public trainings, over the years I have added paid speaking engagements, consulting, outsourcing and most recently publishing a book.

SO based on $, I have achieved my original plans and am able to comfortably move on to the financial goals of my next 5 year plan.

When it comes to working with schools, who represent the future of analytics in the Philippines, I have consistently given talks, been part of activities and mentored interns/OJT.

When I check off the list of schools I have worked with in the past 5 years I can definitely say I have met this metric.

The third data point I look at is number of Filipinos trained.

When talking about public trainings we are about 1000 persons over the past 5 years. When we add the number of attendees of public speaking engagements, the number gets closer to 5,000. And that’s paid events.

If I add the number of students and free events we are getting close to 10,000.

SO, I have fall surpassed my expectations from 5 years ago on that metric.

When assessing the success of a business plan you need to measure data over time to make sure you are making progress.

You also need to be able to make course corrections.

Before the training business started taking off, I did some consulting. To generate consistent revenue, I got into outsourcing.

Both course changes allowed me to continue pursuing my original goal of training Filipinos to use more data in their decision making and to empower analytics centric cultures.

So what are the key metric of your business plan? How do you measure them and make sure you are making progress. Do you have a threshold that you set to make course changes if you are not meeting that threshold?

To effectively execute a business plan, you need good analytics in place.

Dr. Data_Analytics in the Philippines

Analytics in the Philippines – The Philippines is at the center of the action when it comes to solutions to the global need for analytics. Blessed with a solid foundation of young, educated and English speaking workforce, companies around the world are look for Filipino analytics talent to fill analytics positions. DMAIPH was set up to facilitate these solutions and bring the talent and the business together. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can help you take advantage of this unique global opportunity.

 

 

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The 10 Analytics Essentials of Entrepreneurship

A good friend of mine, Boom San Agustin, recently blogged about the essentials of entrepreneurship. Boom listed the 10 things most essential to be successful in setting up and running your own business.

This inspired me to put an analytics spin on each of the 10 points, showing how you can use data to augment each point.

  1. Have passion for what you do. One way to measure how much of your time you are devoting to your passion is to set a schedule and track how much time is devoted to everything you do each day. If you are happy with the % spent on passion projects then you are doing the right thing. But if too much of your time is spent on things you don’t like doing, then you need to make some changes.
  2. Pursue excellence first, money second. Here you need to do a lot of research and ask a lot of questions. You need a clear idea of what excellence in your chosen business looks like. How can you measure excellence with your products, your service, your team’s performance and engagement? Putting some key metics in place will allow you to make more informed decisions.
  3. Be open and honest with others and yourself. Get feedback. See what % of your client, customer, partner, team member, interactions are honest and endure honesty in others. Come up with a way to measure the trustworthiness of what you do.
  4. Have a “can-do” attitude. Keep a project list of all the things you need to accomplish. Update it every day. Be able to show yourself and others your progress towards getting things done. This will ensure that people see the work behind the words.
  5. Be the leader your team needs. Devote significant amounts of your time to your team. Keep them informed by blogging. Build tools for communication like newsletters. Be visible in person and in social media. Track the frequency of your engagements and correlate them to employee satisfaction surveys.
  6. Learn to communicate well. Get in front of an audience whenever possible. Engage the audience. Ask for feedback. Identify challenges and opportunities and then follow up. If your team doesn’t know what is going on in your head, then it is a problem. Gathering data on your communication strengths and weaknesses is key.
  7. Be a teacher and a learner. Facilitate as much on-site training as possible. Get involved in it. Train people yourself on areas you are good at. And then sit and listen to other experts in areas you are not. Track the time put into training and come up with a cost justification. Its easy to cut training when times are tough because its hard to assign a value to it. Make this a priority now so you always know the valued of training in your business.
  8. Have your ear to the ground. Stay engaged in person and on social media. Keep updated on trends affecting your business and your employees. Use a social media tool like Hootsuite to manage your social media messaging to get feedback all in one place. Lots of data points can be created and tracked to measure how close you are to the pulse of your business.
  9. Be dynamic and open to change. Set a check-in schedule. Encourage one on ones and team meetings that are not just one sided but empower sharing. If you are open minded and listen, you will be able to make changes to your business that keep things on the cutting edge. Use a timeline to show where you have been, where you are and project out where you are going.
  10. Know when to quit. We all fail. Businesses will all fail at some point. Winners know when its time to fail and walk away to do something else. Losers stay the course until they go down with the ship. Figure out what is the most important metric in your business. Sales, profit, engagement, risk potential… whatever it is. Figure out what is the lowest acceptable number, once you get close to it, be prepare and exit plan. If you pass it, face facts and pull the plug. Always have that data point at your fingertips.

If you are able to build in analytics like these, you will be able to manage your business well. You will set a tone among the leadership that uses data, not just the gut, to make decisions. One of your first hires should be a data guy who can build a business dashboard and deliver impactful reports. Someone who can help you identify risks and rewards and keep your focus on the metrics that matter most.

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Analytics Leadership – DMAIPH specializes in arming the Data-Driven Leader with the tools and techniques they need to build and empower an analytics centric organization. Analytics leadership requires a mastery of not just analytics skill, but also of nurturing an analytics culture. We have guided thousands of Filipino professionals to become better analytics leaders. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to discuss a uniquely tailored strategy to ensure you are the top of your game when it comes to Analytics Leadership.

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.

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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.

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.

Mixing Technique With Empowered Curiousity

Last year I spent some time helping a couple of schools build more analytics centric training into their psychology curriculums. The goal being to help prepare future HR managers and analysts to be ready to deal with real world analytics challenges.

Over the next few blogs, I will share several of the topics I listed in these curriculums that are equally balanced in both the technical and intellectual aspects of HR analytics.

It is a common misconception that HR analytics is all about using tools and techniques to generate reports and share information to management in a way that makes the business more successful. This concept will not generally work because the analysts are not empowered to question, explore and discover new opportunities or to understand hidden risks. All they are expected to do is report things faster and with more flash.

Some of the topics typically taught in your basic HR and/or Recruitment Analytics class include:

  • Stages of HR Analytics
  • HR Metrics – Calibration and Measurement
  • Statistical Analysis Tools like DCOVA (define, collect, organize, visualize and analyze)
  • Enhancing HRIS (Human Resources Information Systems)
  • Optimizing MS Excel for HR Analytics
  • Business Intelligence Tools for HR Teams
  • Predictive Analytics Methods and Models
  • Big Data Analytics for HR Teams

Each topic can be its own training module if you have the time to sit in a class and approach the use of HR analytics academically. The problem is few of us can spare the time.

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My solution is a mixture of self-education, internal team building dynamics and an empowerment based model of analytics training that will not just make your team better at building reports, but will unlock their minds and free their curiosity allowing them to get outside the box and discover things you can’t even imagine.

No one wants a team of drones who just follow steps in a technique or use a technology to do just exactly what it was designed to do. To really have an HR Analytics team that make a difference, you need a team that thinks differently. If you are serious about building this kind of culture in your business, then I can show you how.

Analytics Culture – The key to using analytics in a business is like a secret sauce. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization. A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story.

When Your KPIs Aren’t Really KPIs

One question I get asked a lot is what should someone do when they know the data they are reporting and/or using in their analysis is not the best data to available?

No matter what part of the business you work in, the first thing to do is to define the current Key Performance Indicators (KPIs) being used in decision-making.  Often right off the bat, some of the KPIs being reported aren’t even being used.

You can do a simple survey, asking end users to rank in order of importance the KPIs they get. Also ask if the ones at the bottom are even useful or should they be eliminated if no one is using them.

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At the same time you should be working on understanding what computations go into each KPI. Often we just do simple counts, total and averages that mask more important data. On the flip side, we tend to over complicate things with extravagant weighing and scoring. Either way, we need to make sure we know exactly what is being reported and how does the final data point come to its end state.

The next step is to look at the data architecture to make sure there is nothing happening upstream that might impact the data we are using in the KPIs. Before making changes to the KPIs we want to have the full view of what happens before the data gets to the end user.

Now we are at the point where we can start experimenting. What happens when we swap out data points? Or if we change a variable in a calculation? Or we pull the data from a different source? The questions are endless. Pick a few, make some changes in a test environment and start sharing the updated KPI data. See if it has more value with the end users.

Again, this shouldn’t be hard. But of course in many organizations a lot of consequences can result from a simple change to just one KPI. Spreadsheets may have to be reformatted, review processes may have to be updated, dashboards may have to be redesigned. But in the end, what is more important… making decisions with crappy data or setting a standard to let the reporting process evolve as the business evolves?

This come back to my point earlier, changing KPIs is as much sales as it is analysis… that you have to be ready to share a story, back it up with data, and really influence the minds of senior management that updating the KPIs makes good business sense.

If you are at a point where you are trying to figure out what KPIs aren’t working anymore or you need help is building a business case to change some KPIs, let me know. I’m here to help.

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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. 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.

Recruitment Analytics: A Simple Classification System

How do you classify the applicants in your pipe line? There are hundreds of ways to separate resumes at the first point of contact by potential job fit. Most Applicant Tracking Tools have this built in and really smart ones will auto separate and classify based on keyword searches.

If you can afford an ATS or have veteran recruiters and/or an optimized process you are probably already doing this. But you would also be shocked to know how many companies are not doing this.

To get started just create 3-4 piles to put resumes in. Its as simple as this:

  • Pool A is for candidates who have most if not all of the qualifications you are looking for.
  • Pool B is for applicants who have some of the qualities.
  • Pool C is for applicants who really don’t have any of the things you are looking for and/or have some fatal flaws that you believe are incompatible with the job.
  • Pool D can be for resumes who currently don fit, but might in the future.

If you are just using Excel to track your applicant pipe line, it is easy to add a column for general classification. Through in some weighted scoring to rank within each category and you are actually doing better than a lot of small and medium sized companies.

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Just as an example, In each pool, you can add a rank of High, Medium and Low. High being they should be ready to start day one, medium meaning the will need some training time if they are hired and low meaning they will need some extensive training.

It is really that simple. Starting adding structure to your recruiting so you can focus your time and energy on those who have the most potential to help you right now, but also keep track of those who might be able to help you down the road.

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If you don’t have a good ATS, then doing something like this will make a huge difference. You will soon be able to start making more strategic choices on who you spend your time, focus and money on.

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.

What Exactly Are Recruitment Metrics?

A general definition of recruitment metrics is something like this, “standards of measurement that HR and Recruitment professionals use to identify, analyze and present important information regarding the hiring process.” Recruitment metrics are extremely important in both assessing the effectiveness of the recruitment process and in looking at the ROI (return on investment).

Traditionally recruitment metrics focus on two areas; cost per hire and time to hire. They are both looking primarily at only the impact to hire someone.

However, those metrics generally do not include a multitude of important data points that decision-makers need to know. For example things like candidate satisfaction and hiring manager satisfaction can help determine wholes in a process.

You can also use recruitment metrics to optimize the hiring process looking at things like distance to work, difficult of commute, and demographic data on what schools and courses provide the best employees.

Another are you can draw psychometric data from for your metrics would be on things like work ethic, career decision-making and employee loyalty to see who is successful in your company so you can find more like them.

The types of metrics you can use in your recruitment process are practically limitless.

Based on a recent survey I saw on LinkedIn, If we use metrics correctly, they achieve the following additional benefits:

  • Advance the relationship between recruitment and the hiring managers — align the RIGHT objectives
  • Provide credibility to the recruitment department by displaying that they understand the overall business goals and objectives
  • Define what is important and expected of each recruiter
  • Drive consistency in delivery of recruitment services to the organization
  • Provide a platform to measure recruiter accountability and performance.

Does your recruitment process have actionable metrics that can drive data-driven decision-making?

If you are having trouble with your recruitment metric, connect with me and I’ll help you make sure you are measuring the recruitment metrics that are key to your 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.

What To Do When Employees Don’t Succeed?

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Came across this interesting article on LinkedIn, about what to do instead of firing an employee. It caught my attention as the BPO Industry in the Philippines continues to grapple with attrition rates that are way to high.

In short, the problem is that with a perceived deep talent pool to tap, BPOs have put little effort into retention policies instead being quick on the trigger thinking they can easily find a better employee. This mindset is not only self-destructive but also badly out of line with available data. As it gets harder and harder to recruit quality employees, many times the answer is pour more money into recruiting or more money into incentives, but almost no one is putting more money into training and coaching.

When you can step out of the industry for a minute and look at the patterns its pretty mind-boggling that such a booming and vibrant industry is so short-sighted.

So, with that back drop in mind, I found this article a good one to help me and my management team put some pauses in place and do a little more due diligence before coming to the decision to give up on someone.

The 4 bullet points listed are all very good ones to chew on:
1. Employ Self-Assessments to go hand in hand with KPI data points
2. Setting clear and achievable goals to mark success
3. Targeted coaching and training
4. And redeployment to positions with a better chance for success

I’ve added these discussion topics to my next management meeting agenda and will build in additional check points within our assessment process. All in all a good read indeed!

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.

One of my favorite blog posts from the past year! Know the Difference Between Your Data and Your Metrics

http://blogs.hbr.org/2013/03/know-the-difference-between-yo/

Know the Difference Between Your Data and Your Metrics

How many views make a YouTube video a success? How about 1.5 million? That’s how many views a video our organization, DoSomething.org, posted in 2011 got. It featured some well-known YouTube celebrities, who asked young people to donate their used sports equipment to youth in need. It was twice as popular as any video Dosomething.org had posted to date. Success! Then came the data report: only eight viewers had signed up to donate equipment, and zero actually donated.

Zero donations. From 1.5 million views. Suddenly, it was clear that for DoSomething.org, views did not equal success. In terms of donations, the video was a complete failure.

What happened? We were concerned with the wrong metric. A metric contains a single type of data, e.g., video views or equipment donations. A successful organization can only measure so many things well and what it measures ties to its definition of success. For DoSomething.org, that’s social change. In the case above, success meant donations, not video views. As we learned, there is a difference between numbers and numbers that matter. This is what separates data from metrics.