Category: Analytics Leadership

The 3 Pillars of Small Business Analytics

When I consult with small business owners, there are 3 areas where my guidance generally has the most impact. I call these areas the 3 Pillars of Small Business Analytics.

The first pillar is a Competitive Landscape. I have found that very few small business owners really have a handle on the competition.

A competitive landscape analysis will reveal threats and opportunities that generally are not obvious to a business owner who focuses most of his/her energy on running the business itself.

Some of the data points you can capture and analyze include pricing, location, business size, quality, scope of business, diversity of product offering and of course revenue.  You would be surprised to find how easy it is to gather all this info.

Knowing where your products and services stack up against your competition is a key to prosperity. To achieve this understanding you need to use analytics.

The second pillar is a Demographic Profile. I have also found that very few small business owners really understand the demographics around their business.

A demographic profile analysis will illustrate how closely your customer base mirrors the actual population around your business. In many cases small businesses are not positioning their services correctly based on the opportunity in their market.

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Data to include would be traditional demographic markers like age, race, sex, family status, financial status, economic state, etc. There is a ridiculous amount of data on the internet that can be mined free and easy.

Making sure your business is properly positioned to take advantage of your arket will ensure more long term success. The data is out there; you just need to know how to bring it into your analytics process.

The third pillar is Customer Insights. With the boom in social media, most small businesses have not figured out how to capture and analyze all the information being published and shared about their business.

Customer Insight analysis allows a business owner to stay on top of problems and identify how customers feel about their business quickly.

We all know how quickly things can go viral and having a good tool to capture customer sentiment in social media is generally the most overlooked aspect of running a small business.

Positive and negative reviews, trending items, number of likes, follows and shares, are all items that can be rolled into customer insights. You can combine this with surveys, focus groups and loyalty programs among other things to get a full picture of your business.

If you are a small business owner, decision-maker or analyst then focusing on these analytics pillars will make all the difference in the world.

And the best part, is they are all free and easy to bring into your business.

Small Business Analytics – The field of small business analytics is just starting to blossom as companies are looking for more data-driven decision-making to prosper in the age of Big Data. DMAIPH is at the fore front of providing analytics training, consulting and outsourcing options to small businesses. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation on how to get more analytics in your small business.

 

 

 

 

Being A Great Analyst > Key Attribute #4 > Be Enchanting

If you are a good analyst or a decision-maker that uses analytics, being enchanting makes your job much, much easier.

One key to using data and analysis effectively is understanding how to enchant people by being likable, trustworthy and using data and analysis to further a great cause.

A few years back, I came across a book by Guy Kawasaki called Enchantment. It is my all-time favorite business book.

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Guy Kawasaki is a marketing expert and used to be Apple’s Chief Evangelist (aka Chief Marketing Officer). At Apple their goal is to convert customers to being loyal to Apple products for life.

In Enchantment, Guy talks about how Apple and other successful companies are able to create enchantment in their customer base that fuels passionate and long lasting relationships.

As an analyst there are many lessons that you can draw from Enchantment to being an incredibly impactful member of your organization.

One of the pillars of Enchantment is being Trustworthy. As an analyst, you have to be trustworthy for people to want to follow the direction your data and analysis point.

Your data has to be clean, valid, and accurate.

Your analysis has to be easy to understand, easy to replicate and easy to boil down into a few bullet points.

When you accomplish these things you are creating trust. Getting decision-makers to listen to what the data is telling them comes when the analysts have their trust.

That’s just one part of Enchantment. I use many examples of how to apply Guy’s concept to data and analysis in my training classes and in my company.

If you are looking for a way to add value to your company, which in turn can make the business more successful then this book is a must read.

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.

Analytics for the Small Business

Analytics is about looking for patterns in data to help answer questions. Most businesses use analytics to help ensure more data-driven decision-making.

No matter the size, scale or scope, every business generates a wealth of business data. Every business has an opportunity to uses that data to drive more intelligent decisions.

The primary people responsible for conducting analytics on the massive amounts of data we have today are analysts. Analysts are skilled in using various technologies and methodologies to identify, inventory and integrate large amounts of data quickly.

The term analytics can often be used interchangeably with statistics and data science. What separates analytics from disciplines like statistics and data science is generally the speed of the analysis and the focus on solving business problems.

The most common form of analytics is business analytics that are generally used by owners, senior leaders and decision-makers to investigate problems, validate assumptions and to guide strategic planning. As a generalist, business analysts can help in a number of areas of the business.

Business analysts are therefore the most common type of analyst, especially in a small business. If you do a job search on the title analyst, as many as half the posting will likely be business analysts. However, analytics can be used in an almost limitless number of business functions in specific areas like HR, recruitment, marketing, finance, and so on. Each one can have its very own analyst.

Analysts have been around a long time, but recent technological advances have both allowed us to produce and capture more data as well as give us the ability to analyze immense data sets quickly. Thus we are amidst a huge boom in the applications of analytics and the need for analytics talent across the globe. Analytics is something just about every business leader is trying to figure out how to use more effectively in their business. To add to our challenge, the demand for good analysts is booming just as fast as the explosion in big data.

As a result, there is a huge shortage of people who are skilled in working with data to answer questions and solve problems. This is why you have seen the number of analyst job postings increasing at an amazing rate. In the first few chapters of the book we will discuss the quickening demand for analytics talent and why it is so hard to find good analysts, especially at the small business level.

If you are a business leader, manager, owner, and/or executive are not actively trying to surround yourself with analysts and if you are not infusing an analytics centric culture in your business, you will most likely soon see your business fail.

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A small business needs analysts to make sense of big data, manage the storage of the data, and know when to use which of the 3 types of analytics (descriptive, predictive, and prescriptive). To be effective, analysts need to have business intelligence tools to create data visualizations and build business dashboards.

If you need an analyst or want to be trained in analytics, connect with me and I can show you how to get started.

Small Business Analytics – The field of small business analytics is just starting to blossom as companies are looking for more data-driven decision-making to prosper in the age of Big Data. DMAIPH is at the fore front of providing analytics training, consulting and outsourcing options to small businesses. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation on how to get more analytics in your small business.

Most Analysts Are Spending Only 20% of Their Time on Reporting

In many cases reporting is either something that is set and stone and just needs to be filled or there is a time crunch forcing quick and dirty reporting.

Little time is devoted to using the data for storytelling, maximizing data visualization and really providing the audience exactly what its needs.

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

Ideally, at least a third of the time should be spent post data gathering and analysis to really give the end user of the data the things they need for intelligent decision-making.

A full one-third only spend 10% of their time on reporting, which to me means that there is a lot of the waste in their analytics process.

If you take a full 40 hour week to complete a high priority, high value report but only have Friday afternoon to boil down your finding into a report, it is highly unlikely that your report will fully capture the fruits of your labor.

However, if the time frame is even shorter… you have to do all this in one day, you are just getting to the reporting phase at around 3:30pm.

You have less than an hour and a half to summarize you methods and boil your findings into a few points.

Making sure you craft a compelling story to really influence decision-making based on intelligent data analysis is likely impossible.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

 

 

The Analytics of Measurement and Evaluation

By taking inspiration from the way corporations use business analytics to optimize their Big Data, our Program Measurement and Evaluation processes can be greatly enhanced.

To understand the connection, let’s start with the mission of the Measurement & Evaluation program.

“The ability to effectively evaluate projects, programs and processes is becoming increasingly essential to organizational success today. American University’s online Master of Science (MS) in Measurement & Evaluation provides you with the knowledge to lead these evaluation efforts and the technical skills needed for analytically demanding roles in upper management.” 1

A good analytics solution constructs a universal framework for collecting, analyzing and utilizing data to determine project effectiveness and efficiency.

Likewise, an efficient measurement and evaluation of projects, programs and policies using analytics should ensure success. An analytics centered approach will likely work with corporate, non-profit and governmental organizations across various sectors and industries.

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We can look specifically to two key business analytics concepts I have used in my twenty plus years of analysis work; Key Performance Indicators (KPIs) and Data Visualization. The key to my success was my ability to answer important business questions using analytics.

Analytics is generally defined as the discovery of patterns in data that provides insight and identifies opportunities. As Carly Fiorina, former CEO of HP said about analytics, “The goal is to turn data into information, and information into insight.” 2

Organizations that invest in analytics generally make much better business decisions then one’s that don’t. In fact, IBM found that organizations who use analytics are up to 12x more efficient and 33% more profitable. 3

In the corporate world, business analytics is widely use to track, analyze and report Key Performance Indicators (KPIs).

KPIs are rolled up to senior leadership to drive business strategy, identify and mitigate risk and to optimize operational productivity.

This approach is very similar to the way projects in the Measurement and Evaluation are tracked, analyzed and reported.

So we need to ask ourselves, what are the KPIs for the project, program or process we are measuring? What points of data need to be captured, analyzed and reported to determine success?

A successful analyst is able to remove the noise when analyzing data and isolate what matters most to his or her organization. That is what is at the heart of measurement, knowing what data is important and what is not.

Once we have the right data, we can measure what the data tells us to determine success, causality, impact… whatever the outcome may be.

A quote often attributed to management guru Peter Drucker perfectly sums up why big corporations rely so heavily on analytics when he said “What gets measured, gets managed.”

Similarly, policy decisions can be made based on what is measured. Project funding can be impacted by what is measured. Process optimization can be directed by what is measured.

Once we are able to measure what is truly important to policy-makers, managers and decision-makers, we need to make sure we present the data in a compelling way.

This is where data visualization comes in.

I often make the analogy that if a picture is worth a thousand words, then a good pie chart is worth a thousand rows of data.

We all know that most people learn more by seeing something then by reading or hearing it. Data visualization takes that a step further.

Data visualization is not only important to presenting our insights but also for exploring the data for insights. Most people find it easier to process information when it is in the form of a picture then a collection of data.

Chip & Dan Heath, Authors of Made to Stick, found that, “Data are just summaries of thousands of stories – tell a few of those stories to help make the data meaningful.”

The ability to take all of the data gathered in the measurement phase and use it in the evaluation phase will make a significant difference in the success of the project, program or process you are working on.

According to the Office of Planning, Research and Evaluation, “Program evaluation is a systematic method for collecting, analyzing, and using information to answer questions about projects, policies and programs, particularly about their effectiveness and efficiency”. 5

Data Visualization can be used to paint a picture of a program, project or policy that influences outcomes based on the KPIs. And by appealing to the basic human fascination with stories, a persuasive graph, chart or infographic can make all the difference in the world.

By adopting the business analytics concepts of KPIs and Data Visualization, and applying them to the world of programs, policies and projects, you can find the same level of success I found in the corporate world.

  1. American University, “Certificate in Measurement & Evaluation” http://programs.online.american.edu/online-graduate-certificates/project-monitorin Accessed October 20, 2016
  2. Carly Fiorina Speech from December 6, 2004 http://www.hp.com/hpinfo/execteam/speeches/fiorina/04openworld.html . Accessed October 20, 2016
  3. Simon Thomas, Senior Analytics Consultant for IBM https://youtu.be/Zi8jTbXnamY . Viewed October 20, 2016
  4. Chip & Dan Heath, Authors of Made to Stick, http://heathbrothers.com. Accessed October 20, 2016
  5. OPRE, http://www.acf.hhs.gov/opre/resource/the-program-managers-guide-to-evaluation-second-edition. Accessed October 20, 2016

Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.

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.

DMAIPH Quick Data Survey

A few months back I sent a quick survey to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Here is the question I asked.

Greetings!  I’m hoping you can help me gather some data for a book I’m working on. If you had to breakdown the work you do into 3 buckets; finding data, analyzing data and reporting data, what would the % of each be? A quick reply with your breakdown would be hugely helpful in my research. Thanks!   Dan Meyer, Analytics Champion, www.dmaiph.com

I got back over 400 replies.

Here is how they broke down.

 

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

The higher the %, the more each analyst spent time doing that particular phase of analytics.

Here are some of my takeaways from this simple (and very nonscientific survey)

  • I was surprised to see 45% spend half their time or more on finding data. To me this is one of the telling signs that Big Data has led to a shortage of top analytics talent.
  • Only 1 out of 4 analysts are spending 20% of less of their time finding data. These are generally senior analysts, well established in their company.
  • Only half of my analyst connections are spending 40% of more of their time on conducting analysis. With significant time spent on finding and/or reporting data you can imagine a lot of important discoveries are being missed and opportunities lost.
  • Only 1 out of 3 analysts are getting spend my recommended 50% or more of their time actually doing analysis work.
  • Based on my survey, reporting gets shortchanged a lot. All in, 96% of respondents spend 30% of their time of less on reporting.
  • My recommendation is that you spend about 30-40% of your time on the reporting aspect, and sadly only 4% of my analytics connections are able to do that.

In an ideal world, I would expect an analyst to spend no more the 30% of their time on finding data, and at least 30% on reporting their findings, leaving more or less 40% to do the actual analysis.

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This breakdown is based on my own experience as an analyst as well as seeing how analyst working for data-driven companies work.

Only about 30% of my 400+ analytics focused LinkedIn connections come close to meeting my recommended breakdowns.

Which means I have a lot of work to do.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

 

Outsourcing Tips for Small Businesses

Small Business Analytics is not a very well established discipline.

You generally see analytics across all kinds of businesses in just about every industry, but for the most part these businesses are large in size.

The concept of analytics is something that most small businesses have not embraced because of two perceptions that hinder the adoption of best practices; a good analytics solution is too time consuming and too expensive.

These perceptions are often false. Just about any small business can benefit from a number of analytics techniques and technologies that do not require significant amounts of time or financial resources.

When talking with a small business owner about their business, I like to ask a series of questions to gain and understanding of the data they have to work within their business.

Generally, I find that they rarely, if ever they even think about the data they have.

So that is often where we start. Trying to map out their data environment.

Once we have an idea how data is (or could be) collected and stored, then we can turn to talking about analysis.

And after I have a good idea of what (if anything) they are doing with their data we can move to reporting. How is data and analysis presented within the business.

14045878_10154480087262425_4779154686875783746_nOften I find that pieces of the data collection, storage, analysis and reporting process are happening in subtle ways that don’t, on the surface, look like an analytics solution.

Over the next several blog posts in this series, I will offer up some tips to small business leaders, managers to point out where more analytics can be used with minimal time or cost impact to themselves.

To date I have helped over a dozen small businesses come up with an analytics solution tailored to their unique needs. We have been able to address key challenges that only a deeper understanding of the data in their business can uncover.

Analytics Outsourcing – DMAIPH has successful set up Filipino analytics teams for over a dozen U.S. based businesses. Offering both virtual and office based teams that specialize in problem solving using data, new technology and analytics techniques is our strength. Finding and empowering analytics talent is increasingly challenging, but we have it down to a science. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn more about how to set up an analytics-centric team in the Philippines.

 

When They Go Low, We Go High

When They Go Low, We Go High

Michelle Obama’s quote from the recent Democratic convention will go down as one of the greatest quotes ever.

And I’ve been thinking about what that quote means for me as an American in the Philippines.

I often talk about why I love the Philippines and how I have so much faith in the Filipino people.

My passion comes from way down deep and is has been unshakeable during my 5+ years of living in the Philippines. Talking about analytics in the Philippines has been the time of my life.

Although there have been bad times. Burned by bad partners, taken advantage of by greedy individuals and flustered by arcane bureaucracy. But they haven’t stopped me.

Because when others go low, I keep going high.

Trying as much as possible to do the right thing. Valuing integrity and accountability over success and profit. These things are the high road.

As a guest in the Philippines, I strive to show appreciation and gratitude whenever possible for the once in a life time opportunity to chase my dream of empowering Filipinos with analytics.

There have been and will be detractors. Roadblocks and hurdles will continue to be a burden. Perhaps even a rift between the governments of my home county and my adopted country may cause more challenges.

But as long as I keep going high when things go low, I will survive.

My faith in the Filipino people has not diminished.

In fact, it has only gotten stronger.

My Analytics Story – My passion is solving problems by bringing together the best talent, cutting edge technology and tried and true methodologies. DMAIPH is all about empowering people towards better Decision-Making through the use Analytics and business Intelligence. This is what I do best. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly for a free consultation about getting more analytics into your career and your business.

The Stuff of Legends

The 2016 San Francisco Giants beat the odds.

After having a horrible second half of the season, even the most die-hard Giants fans were on the edge of giving up.

But they persisted.

They didn’t give up.

The keep fighting until the last day of the season.

Then they made the playoffs.

And they beat the odds again and beat the New York Mets.

They got their shot and they made it.

Now they have even bigger odds facing them to beat the Chicago Cubs.

You can look at all the data you want, but sometimes it just comes down to things hard to measure.

Like heart.

Like persistence.

Like belief.

You need these things to make it.

I love data and use it all the time, but sometimes in life you just can’t explain how some can beat the odds.

Like the 2016 Giants.

This is the stuff of legends.

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.