Tag: Why Analytics Fail

Why Analytics Projects Fail – #11: No End User Participation

One the most overlooked and under appreciated parts of assuring a successful analytics implementation is getting the participation of end users. End users being defined as the consumers of either the data, the analysis and/or the reports that come out of the project.

I can tell you countless horror stories about stacks of reports that go unread, email summaries that are never opened and business dashboards that are rarely clicked on. In most cases, all because the end user was not involved in the project or its development process.

One example of this is when the ones who need the reports are not asked what they need in the report.  This is more common than you might think. Requirements, no matter how well thought out, will always overlook something someone needs. Another reason is not finding out how the end users want it to look. They often are omitted from the design phase and just left to use it. Worse it’s possible that what is delivered in not even compatible with other things they do. This leads to failure by not being useful, a complete waste of time and resources, especially yours.

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The best way to assure end user use is to have them involved at the earliest stages of the project. If you are selecting the project team or have influence on the team makeup, make sure you get an end user who can speak for that audience. It might be more than one person.

Another way is to keep the end-users informed and allow for feedback. Finding ways to work feedback into your project is another place you would be surprised by how often it is not done.

And finally make sure you build in a testing period before your project goes into production. In some cases this might include the feedback phase, but in big projects there is often a need for end user testing. If you don’t shepherd this effort, who will?

If you are no sure how to go about involving the end users and/or are not sure of who all the end users might be, then you should really answer those questions as early as possible. No one wants to see their hard earned work just end up in the trash bin because it does not fit the need it was designed for.

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 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.

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Why Analytics Projects Fail – #9: Bad Data

In my experience, most of the time analytics projects fail its generally traceable back to a purely human problem. However, sometimes you see things fall apart because of technology, the misuse of technology and/or just bad technology. This is the case when projects fail because of bad data.

There are a lot of ways bad data can happen.

One common way you end up with bad data, is the data was not captured correctly. Perhaps the data was manually input with lots of error. Or maybe your data is not consistently collected so it has gaps. Knowing what exactly goes into capturing your data and being able to understand how it is collected is extremely important.

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Another cause of bad data is that you are not getting all the data or you are getting data that has been altered. A lot of times when data passes from the collection point to you, it might be being truncated, or blended, filtered or converted. Lots of databases are structured for optimal data storage, not usage. A lot of database admins who don’t really know the data will add data flow shortcuts. Or maybe the fall under the datakeepers category and partition or cut out some of the data you need.

Bad data also comes in the form of old and out of date data. When you are making decision on data that just not recent enough, it can lead to a lot of problems. Keeping data fresh is something some companies just don’t value. If that’s the case, you will likely see your analytics initiatives come up with analysis that points you in the wrong direction.

In all three of these examples, one solution I suggest to mitigate the chance you have bad data is to build a data map. Learn about every point in a data flow that touches your data. Talk to the ones in charge of each touch point to make sure your data is not being impacted in any way that can result in bad data. Even if you cannot fix the problem, understanding it can help you set more realistic expectations of what your analytics project can achieve.

I have found using Visio to build data flow visuals is the best way to explore, document, and report how the data being used in my projects is being impacted by the environment it lives in. Knowing Visio is a valuable skill for an analyst. If you don’t use it, I promise you that once you do you’ll be sending me a thank you.

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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 – #8: Lack of Resources

To start with a lack of resources should probably be called lack of time. Lack of time to design an effective strategy. Lack of time to find the right talent. Lack of time to get everyone on the same page.  We are all just too busy and have too much to do. We say lack of resources, but mostly we mean our team doesn’t have time.

A lot of times you hear about failures with analytics projects is because of lack of resources. When I hear about this, I always ask for a better definition of what is meant by lack of resources. Is it lack of leadership support, lack of funding, lack of strategy, lack of focus and vision, lack of talent? They are all often disguised as lack of resources.

In each of the previous seven blogs in this series I talked about a reason why analytics projects fail and since they can all fall under the boarder lack of resources, let’s do a quick recap.

  1. Lack of Focus – People are not on the same page
  2. Lack of Vision – People don’t know where this is going
  3. Lack of Management Support – People don’t know who to follow
  4. Lack of a Champion – People have no one to cheer lead
  5. Lack of Organizational Support – People don’t really care
  6. Lack of Funding – People don’t want to waste money on this
  7. Lack of Talent – People can’t do the job

There are all people driven reasons for why your project may be in danger of failing. They are all fixable using people skills. This is why I often argue a good analyst who can communicate is worth more than a great analyst who cannot. The reasons why analytics projects most often fail is human, not technological.

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In the end, for whatever of the reasons above, your project is in jeopardy, it will be up to you to show people why they should invest the time needed to get things back on track.

You have to push for focus, share the vision, educated your managers, become a champion, gain organizational support, secure funding and align the right talent to make things work.

I have been in this situation numerous times. In every situation the one constant variable that changed possible failure into a success was me. Bring a truly great analyst means showing people how your project will be a solution to their problems and is well worth their investment of time.

When you do this, they you won’t be in a place where lack of resources dooms your analytics project.

#IamDMAI

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 – #7: Lack of Talent

When analytics projects fail due to lack of talent, this is generally symptomatic of a bigger cause. Lack of talent is something that can be much harder to fix then just hiring someone.

One of the reasons behind the lack of talent may be a misunderstanding of the project by senior leadership or just an overall lack of management support. As I mentioned in a previous blog, the best thing you can do is work with a senior leader to help them understand what level of talent is needed. When you do this you can enhance your analytics solutions and have them advocate for you to get the right talent.

Lack of vision and/or focus by your organization can also result in not having the right talent available for the job. It might not even be the analyst, but the it might be something missing within the development team or the project implantation team. This generally ends up with analytics solutions being full of patchwork shortcuts that limit their impact.

Lack of funding can also be an issue, where your organization just can’t offer a competitive package to the available talent. This is becoming even more of an issue lately as good analytics talent is in high demand and the supply can’t come close to keeping up.

Having the right analyst, with the right skills sets, the right training and the right tools aligned to give your business a good analytics solution misfires a lot. There are hundreds of business intelligence tools, thousands of types of databases, all generating very unique reports. When one of these elements does not match up it can easily cause a failure due to lack of talent.

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My suggestion if you think you have a lack of talent problem is draw some kind of process flow. Who are all the players in each part of the process? What applications are used to collect, store, analyze and report your data? What programming or language skills are required?  When you lay all this out then you have an idea of what skills and experience your analyst needs. Combine this with the people side of the job, what communication skills, what data visualization skills, what project skills does your analyst need? If you don’t have anyone in the organization with this list of skills, you need to either hire one or create one.

When you look at job postings right not for analysts, its easy to see that requirements vary greatly across positions.  No two companies have the exact same analytics needs not employee analysts the exact same way. So if you are going out to hire one, make sure you have a clear idea of what you need and not get caught up in looking for an analytics rock star.

It is often easier to actually look inside and find someone who can be trained to take on the role. Having internal business knowledge and knowing the organizational culture are huge plusses. A lot of time because that person doesn’t have the skills on their resume yet, they get excluded. However, I have always favored promoting from within and upskilling then going out and hiring an unknown variable.

So if you think lack of talent is killing you analytics project and are not sure what to do next. Connect with me. Let’s build a job description that tailor fits your needs and see where the best place is to find them. It’s probably someone sitting in a cube next to you.

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 – #6: Lack of Funding

Of all the reasons an analytics project can fail, one of the hardest to fix is lack of funding.

There are numerous causes for funding issues with an analytics project, 3 of the most common being unexpected budget cuts, shift in strategy, and lack of understanding.

When you are faced by unexpected budget cuts, which has happened to me several times, the best thing you can do is try and reconfigure your project so that as least pieces of it can still be completed. The idea here is to do what you can until more money is made available.

Having a well thought out plan that is scalable will help you tremendously. One time when I had a million-dollar dashboard project cut because of budget cuts, I peeled back some features and redesigned others to come up with a new plan for 10% of the original cost. That was approved. And over the next year I had pretty much added everything cut back piece by piece. Bottom line, if the company needs a new analytics tool, its up to the analyst to make sure they get it by being flexible and smart.

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A shift in strategy happens a lot in business. So many internal and external forces are at play, a lot of times what once seemed a priority, can quickly become an afterthought. With analytics this can happen a lot when people fall back the we can just get by with what we have for now mentality. In today’s business world where success is driven by data, this can be crazy but it still happens everyday.

The best way to react to strategy shifts are for you to adapt your project to the new strategy and keep it both relevant and necessary. A good analyst can always find a way to offer analytics solutions for any part of the business. Use this adaptability to show your project can evolve with the needs of the business and you will likely still get funding, albeit for a new set of users.

The third reason lack of funding can happen, is actually a lack of understanding. Often finance decisions are made based on assumptions and predictive modeling… highly susceptible to being wrong if some important variables are missed. This has happened to me a number of times. But after conversations and educational moments with the finance team, the true value and ultimate savings of my analytics projects led to the lack of funding being mitigated.

Some things you can try when your project is impacted by a lack of understanding will take us back to the concept of enchantment. Make sure they like you and understand what value you and your analysis adds to the team. Often this can be a hard thing to quantify in a budget. Make sure you are showing how this project benefits others and helps the business as a whole… build trust. Third, make sure the project you are championing will make a difference, show that difference and educate on the need for that difference, in short show them you are doing this for a great cause.

There are countless reasons for lack of funding to become a roadblock for your analytics project, and countless ways to remedy this. If you are faced with one and need some help getting things back on track, connect with me and we can come up with a way to get your project funded again.

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 – #5: Organizational Politics

One of the biggest hindrances to the success of analytics projects is something most of us have experienced, organizational politics.

Organizational politics are informal, unofficial, and sometimes behind-the-scenes efforts to sell ideas, influence an organization, increase power, or achieve other targeted objectives. This is what happens when you find yourself being thrown under the bus… taken a fall for someone else’s mistake.

If you are lucky to have escaped organization politics for the most part and wondering just how they can lead to the downfall of an analytics project, let me share with you an idea what that looks like.

Data is horded. People don’t like sharing because its not encouraged or rewarded. In some cases people can be outright mean about it. Keeping data that they know can have a positive impact for others just to hold power over someone. It’s nasty.

This generally comes because senior leaders don’t really see the big picture and don’t share much themselves. This trickles down to the ones with the data and they build castle walls around their information and act as gatekeepers.

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Projects can also be hindered, stalled or killed for no reason other than your boss lost to another boss. I once had a million dollar analytics project shelved because my boss got in trouble with the big boss. Nothing to do with me or my project or its cost or its benefits, it was completely because of something out my control.

When asking around you might hear of an experience like this as well. People hoard, manipulate and/or alter data not because it is being rewarded or encouraged, but because they are afraid being caught red-handed. A good analyst has to be willing to  report the good with the bad.

One area of organizational politics you can control though is your likability. I make the comment a lot, that you have to be likeable to be an effective analyst. If people like you they share data with you, they advocate for analytics, they support you in a multitude of ways.

If they don’t like you, then its gonna be hard to be seen as an asset to the organization. An analysts job is to educate, illuminate, and inspire… you can’t do that with a bad reputation. This is a lesson many of us have to learn the hard way, but once we learn it we can see opportunities to increase our likability factor and actively use them to push our projects forward.

So the outcome of an analytics project you are working with is in jeopardy if you are in an organization rife with office politics. SO short of updating your resume, what can you do to turn the boat around?

Here are 3 things I suggest:

  1. Get buy in from the top. Make sure what you do feeds its way up the food chain. Make sure the top dog’s analytics needs are being met and if they are not show how they can be.
  2. Use your data to show win-wins. Find examples of where if we combined data from one source with data from another source you would have the makings of something even greater.
  3. Buy lunch for the ones hording the data. Extend the olive brand, multiple times if need be. If you don’t stating being the catalyst for data sharing, who will?

If you can start impacting some of the negative consequences of your organization’s internal politics then your analytics projects will start seeding positive change. And that will eventually make all the difference in your success or failure.

If you need help combating some of the office politics in your organization that are hindering you analytics projects, connect with me and we will figure it out.

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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: #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.

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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.