Why Analytics Projects Fail: #3 – Lack of Management Support

Nothing sucks more for an analyst than taking on an analytics project without support from above. Great analysts are generally only great if they have bosses who advocate for more analytics.

If no one at the top really understands the benefits of implementing your project, if the leadership will continue to use their gut in decision-making regardless of what your project achieves, then start updating your resume. This outcome happens often when the company does not have a business culture supportive of data-driven decision-making.

In this day and age, good analysts are hard to come by…. You can make more money and be happier somewhere else. Trust me. The chances of you being able to turn analytics naysayers into big data believers is highly unlikely.

That said, if you chose to give it a try… here are a few thoughts on how to get management to become more supportive of your analytics project.

Watch the Brad Pitt movie Moneyball. It will inspire you. Read the book Enchantment by Guy Kawaskai. It will empower you. Im not joking. You cant do this on your own.

After that, then you need to do a few things.

First find the person in upper management most likely to get on board. Ask them to help you. Show them data that will outline the better new world after your project is complete. Tell them about analytics success stories (like Moneyball). Let them see your passion for data-driven decision-making. You need Brad Pitt.

Next, using the concept of Enchantment, determine what is it about you and your project that will build trust. Will it create more transparency? Will it mitigate risk? Something that demonstrates how this project will increase the level of trust between everyone.

You also need to be likeable. Your project needs to be likeable too. What is it about the project that will make people happy? Who gets a better report, faster and with more useful data? Who gets to start using a business dashboard to make quicker and better decisions? What will each of the stakeholders like about this project.

And then you roll out the great cause. The monetary value generated from implantation. The level of risk mitigated. The better intelligence on competitors or about your market. What will be that great cause?

So now you are in a better position to be Jonah Hiil and go start changing minds and swinging opinions about your analytics project.

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.

Why Analytics Projects Fail: #2 – Lack of Vision

Lack of vision often accompanies lack of focus when good analytics projects come up short or even fail.

The end product produced by the hard work being put into the analytics project has to be championed from top down. If the top dog is not talking about your project and pushing the merits of its implementation, they people will fight getting on board. Their focus will go astray.

Lack of vision is most often caused by a rush to implement a new analytics tool or a need to quickly upgrade reporting. A good analytics solution needs clearly thought out goals and buy in from all stakeholders.

Vision comes from being on the same page. A good project manager can control the vision message and repeat it like a broken record at every project message. An analyst gifted with good communication skills can keep sharing the vision to remind everyone of the benefits at the end of the project. It takes people dedicated to the project to keep it moving.

Vision can be handled like a marketing campaign. A catchy project name, an engaging tagline, a central theme accompanying communications and updates can all keep people focused on the end goal.

If your project is floundering because of lack of vision, then you need to channel your inner cheerleader. It often takes an analytics champion to produce the a positive outcome. And if you are reading this blog, that champion is probably you.

Nothing helps get a vision across better than good visuals… what does the end state look like for everyone involved. Find ways to motivate them with posters, with slogans, with dashboards, with free food. Just keep reminding them where we are going and how awesome it will be when we get there.

Lack of vision can also be an issue when an analytics projects are not well planned out. Maybe the scope was too narrow or too broad or perhaps the technology we are using is obsolete.

Vision is a glimpse of what the future may look like. If I can’t conceptualize why we are doing what we are doing for this project, then we can’t very well share the vision we are supposed to be seeing.

My final thought on dealing with lack of vision, is that no one will be better at fixing this then you. As a data person, you have to be bold in your use of data to push the vision and you have to be brave in taking the lead on sharing the vision as much as possible.

Analytics should be accessible across your organization. If you are in a situation where your analytics efforts are being stymied by lack of vision, connect with me and I’ll help you get things straightened out.

Analytics Culture – The key to using analytics in a business is like a secret sauce that fuels Data-Driven Decison-Making. 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.

Why Analytics Projects Fail: #1 – Lack of Focus

Lack of focus is common reason analytics projects fail. Keeping a focus on any project can be a challenge for companies that are not well organized. If you are an analyst or trying to champion analytics in your organization and are up against a lack of focus, I have some ideas for you.

First off, size really isn’t a factor when it comes to the organizational culture towards being organized. In some cases size makes the problem more apparent, but size can also mean more resources, so in most cases its really not a serious issue.

There is generally a strong correlation be the way data is handled in a business and how organized the company is in other ways. Lots of paper, manual processes and clearly define process flows may look organized, but it’s highly unlikely they deliver the type of data leadership really needs.

Lack of focus often happens when leaders seem overwhelmed and say they don’t have time to dedicate to things like analytics. The first thing you need to figure out is are people resources really stretched too thin or is it more a cultural issue where being too busy is more of a badge of honor.

The best way to deal with overworked teams is to start putting data around what they do every day and come up with solutions to improve time management and delegation. Few people can truly say they have extra time, but everyone can say they need to figure out how to manage time better. A good analytics solution does just that.

Few people can rationally explain why their job would be harder if they had more analytics. So it’s not too hard to get people to buy into the concept of analytics, but to get them to buy into the actual practice you need to be part salesman and part storyteller.

You need to show them the value putting a greater focus on your analytics project will bring to both the business as a whole and to each individual involved in the project. Besides showing data to champion the use of more data, you need to tell stories about how its helped in other places. You need to get them to envision how much better life will be once your project is complete.

Lack of focus can also come when the project is not well thought out of you get scope creep… when additions are made to a project that start distracting people form the original goal of the project. It is hard to stay focused when you don’t see focus in the project itself.

The final point I’ll make is that you also need visible and consistent buy in from the person(s) in charge. If they are not advocating for analytics, then your project will never get the focus from stakeholders and project team members you need then you will fail.

Why I Go Left At The Crossroads

What do you do when you are feeling lost and at a cross roads?

Do you turn left? Its the unknown road less traveled.

Do you turn right? Its the way most people will chose when they chose to change.

Do you go back? Its safer being where you know where you are then when you don’t.

Do you go straight? Its easy to keep going ahead and hoping things work out for the best.

83762577 — When faced with this, what do you do?

Do you look at your data?

Do you find new data?

Do you just ask a friend for advice?

Do you go with your gut?

I’m not one to just ask for advice because that usually I get play it safe and go back.

If I were to just trust my gut it would steer me to the right.

In my current situation the data says, stay the course.

But when adding some new, recent data it says turn left.

So to the left we go.

The Five Stages of HR & Recruitment Analytics

I’ve seen a couple of articles recently espousing a set number of stages in HR and/or Recruitment Analytics. Based on my knowledge, the 5 stages of analytics a people-centric department can experience are the following:

Stage 1 – The Data Dark Age – No analytics at all. Pipelines are either in MS Excel, a very old proprietary data based or maybe even on paper. Nothing is really analyzed, data quality is bad, and reports are pretty useless. Not collaboration exists between HR, Recruitment and other business lines.

Stage 2 – Living in Data Castles – Only a few people use analytics and most key management decisions are not made based on data, but on experience. Every department has data stored within its own data base. Its nearly impossible to share data due to poor data architecture. HR data is incomplete and the recruitment process does not have any dynamic reporting.

Stage 3 – The Flat Data Organization – Some people use some analytics to make some decisions, but its generally inconsistent across the organization. Data is generally historical and used tactically to understand simple patterns and effects. Some of the data castles have evolved to data explorers, venturing out to find and use new data sources, but many castles still remain in the organization. Generally HR and Recrutiment are using a people management and/or recruitment management software. Reports are useful and drive some decisions by management, but there is major room for improvement. Some data leads to buried treasure, but some leads you off the map… data quality is inconsistent.

Stage 4 – Civilized Data Flow – Most decision makers have access and generally use analytics. Several key team members have strong analyst backgrounds. Data is easily shared between teams. Most managers look at data before making a decision, and analysts have a say in business strategy based on their analysis. People are empowered to do their own discovery and analysis. The organization has answers to questions about recruitment efforts and HR trends. Waste is controlled with effective people and recruitment management software. Business dashboards are being used to convey a lot of information.

Stage 5 – Data Nirvana – Every team member from top down knows analytics, has access to the data they need and are empowered to take action on it. There are minimal hindrances to sharing data. It is hard to find a place like this but, when you do recruitment works like a well-oiled machine, HR analytics are predictive and driving recruitment efforts. There is never a question management asks, that there is not a data driven explanation to answer with. Business dashboards are interactive and real time. Surprises are minimal and solutions come quick and founded on business data and insight. Open posts are filled quickly and people stick around because there needs are proactively being addressed.

So what phase is your organization in? Where do you want it to be? I can help you assess where you are and we can design steps to get your where you want to go.

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.

HR Analytics – Curiosity Trumps Technique

I came across an advertisement for an upcoming HR Analytics training a few days ago.

It’s a three-day class that goes pretty heavy into the technical side of HR Analytics. Like most analytics training classes being offered in the market right now there is a lot of emphasis how to gather data and report it. I am starting to see a little more emphasis in data visualization and building more dynamic reports, which is encouraging.

However, no matter what analytics tool you have, and how well your HR analysts are in using the technology, if your HR analysts aren’t empowered to really ask questions and unleash their curiosity on the people data they have access to, then you really won’t see a significant success when it comes to using data.

In addition, if your business is not ready to have an ongoing discussion about how to use the data to improve decision-making at all levels of the organization then you are not going to be successful either. You need an analytics centric culture to really benefit from all the amazing tools and techniques now available to HR teams.

When you look over the agenda of an HR Analytics training class and you don’t see anything about culture, empowerment, data-driven decision-making, or dynamic reporting using interactive tools… then it is highly unlikely you will benefit much from sending anyone to these types of trainings.

If you would prefer to send your team to a training where your HR analysts and managers will not just learn a few techniques and demo a few tools, but really get into what it means to be an HR analyst and how HR can be at the forefront of building an analytics centric culture, then I would be happy to include them in my next HR analytics training class.

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.

Turning Data Owners Into Data Resources

One of the biggest challenges I hear about when I do public trainings is how to get people who are stingy with their data to share it.

My answer is always the same… buy them a doughnut.

Seriously, when I reflect back to what made me a great analyst when I was with Wells Fargo, one of the biggest reason was I made sure all the data guys liked me.

Just about every company has someone who likes to keep their data close. Sometimes it is a result of security risks. But most of the time it is because they just don’t like to share. It is also possible they just don’t like someone on your team. Whatever the reason, you have to get them to lower the gate and let you in to play with their data.

From my perspective, I generally see a few types of data gate keepers who have very different reasons to keeping you out of their data playground.

They are afraid to share the data, because they know the data is not 100% trustworthy.
They are afraid to share the data, because they worry you will use the data to do things they can’t.
They are afraid to share the data, because they had a bad experience with you or someone like you.
They are afraid to share the data, because you play for a different team.
They are afraid to share the data, because you won’t need them anymore.
They can’t share the data because it’s a security risk.

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In every case, even the last, engagement is the key. Share with them why you need the data, demonstrate how much more awesome your analysis and reporting will be if you can include their data.

One of the advantages I have enjoyed in my career is that I really get along with people. I make an effort to be likeable and trustworthy. To be a great analyst, you will need to be likeable and trustworthy too.

And I kid you not, buying them a doughnut and dropping it off at their cube works more often than you might imagine.

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.

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.

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.

Sharing My Analytics Story

Sometimes I get asked to share my analytics story. It’s pretty awesome when that happens.

I’ve have gotten so accustomed to talking about my analytics story that I do speaking engagements, public training seminars and write this blog. Talking about analytics and sharing how I have and do use data to facilitate data-driven decision-making is my favorite thing to do.

A lot of people would like to share their analytics story, but they never feel like they are in the right place to do so.

Some are not confident enough in what they are doing and afraid of looking like they don’t know what they are doing. Well, when it comes to analytics most of us don’t always know what they are doing… the whole point of analytics is discovery and looking outside the box.

Other people chose not to share their analytics stories because they don’t have a complete understanding of analytics in general. They know their niche, whatever they are in charge of back at the office. But they are not part of the bigger data picture in their company.

I have also find that others don’t share their analytics stories because they think what they are doing is to simple or not relevant to a broader conversation. Well, hardly anyone does the same thing as someone else when it comes to working with data. How we use data in our jobs is a individual as how we dress in the morning.

SO, when I speak, or present or write, I do my best to get others to participate. I love to learn about what challenges people are having and help them come up with solutions. A lot of analytics trainings are follow this method or use this technology, but few actually solve any problems. They give you tools but no instructions on how to use them in context of your own data environment.

I have found that the best way to build better reports is to talk about them. The quickest way to build engagement for more analytics is to talk about how to use analytics.

It’s all about taking the data in your head and constructing engaging conversations. That’s why in every opportunity I have to talk about analytics, I finish talking about how to market your analysis and how to make it enchanting to your audience.

I’ll be doing a training in Ortigas this coming June 15 and a seminar on June 22. If you are interested in sharing your story and coming up with some solutions to your data challenges, I’d be happy to see you there.

Who Is Best In Your Organization When It Comes To Analytics?

I am currently sharing a survey asking my LinkedIn connections about what part of their business is the most successful when it comes to using analytics to drive decision-making.

If by chance you follow my blog, but don’t get my LinkedIn e-mails. Here is the survey:

As you may know, I have been working on a book about analytics and the data-driven cultures of companies who successfully use analytics. I have a quick question to ask you that will help me in my research.

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Of the following business lines, which one is the business line in your organization that in your opinion best uses analytics when making key business decisions? (Pick One)

Sales & Business Development
Marketing
Operations
Supply Chain/Inventory
Legal, Risk & Compliance
Customer Service
Human Resources/Recruitment
Strategic Planning
No one really uses analytics in decision-making effectively.

Thanks for taking the time to reply, it will be really helpful.

Sincerely,

Daniel Meyer, Analytics Guru

danmeyer@dmaiph.com

I’d like to validate what my experience tells me are the areas who generally best do analytics. I’m also looking forward to finding out there people see as general weak spots.

I’ll be happy to share the overall results of the survey once it is complete.

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