Category: My Analytics Story

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Bad data also comes in the form of old and out of date data.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.

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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 – #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.

Things Data-Driven Cultures Do

Data-Driven Cultures Do These Things:

  1. They embrace Big Data. They aren’t afraid of it. They relish the addition of new data sources and actively look for more.
  2. Managers use Evidence-Based Management techniques. Just about every choice comes based on data analysis.
  3. Challenges are addressed with Data. When something happens that was unexpected, the challenge is met with a data centric approach.
  4. The right data is being used. A lot of work goes into validating data and keeping it clean and fresh. The concept of having a data lake that supports multiple parts of the business is in place.
  5. The have the right analytics talent. Analysts are empowered to go out and discover not just current challenges, but look for potential ones as well.
  6. The know how to communicate. The sharing of information is done to benefit everyone. You won’t see lots of data trapped in silos. Data has no one true owner.
  7. They take action based on their data and analysis. You don’t see a lot of useless reports that kills a small forest or clog up an inbox with massive files. They keep it smart and simple.

Like most of the blog posts in this series, I took inspiration from Bernard Marr when I came up with this list, adding my own analytics spin.

Data-Driven cultures are a lot harder to find then they should be. In this day and age, every company should have a strategy on how to use data to drive more intelligent decisions, but they don’t .

Success eludes many companies because they don’t have the 7 qualities listed above in place. If you were to ask what they look like it would be something akin to this:

  • Top management is afraid of data. Senior leaders don’t even know how to use MS Excel. There is no analytics champion in the organization to spearhead data projects.
  • Decisions are made based on what worked in the past, relying on experience and gut feel. There is little evidence used to go in any certain direction.
  • When things don’t work out, data and analysts take the blame. You will hear a lot of “why didn’t you tell me” and “I didn’t see it coming” excuses.
  • What data is being used is old, dirty, incomplete, full of errors and doesn’t tell the whole story. Reports are basically useless and just produced to look at what people generally already know. They look for what’s there, oblivious to what’s not.
  • They don’t not share data. They hoard it. They don’t trust anyone else with access to it. The data is stored in unconnected storage places. There is no common understanding how to use data.
  • They fail a lot. Success generally happens by hard work as much as luck. It’s impossible to know for sure what caused what to happen.

It’s not easy to take a company that has little or no data-driven decision-making and turn it into an Intelligent Company, but it can be done. I have done it. I have guided transitions from the stone age to the information age. Let me show you how.

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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 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.

Data-Driven Cultures

Inspired in part by Bernard Marr’s 2010 book, The Intelligent Company, my goal these past several years has been to build and/or be part of data-driven business cultures.

In his book, Bernard advocates for using Evidence-Based Management, that is using the best available data to inform decision-makers. In parallel to this, I have been empowering companies and professionals to empower decision-makers to use more data as well. I call it data-driven decision-making, but at their cores, they are very similar approaches to managing success.

Over the next several blog posts I will share my thoughts on the steps Bernard published. I will be giving my own spin towards more analytics and data-science, two things that I think have accelerated in importance since the book went to print six years ago.

The cornerstone of the book is the five steps to more intelligent decision-making, which are:

  • Step 1. More intelligent strategies – by identifying strategic priorities and agreeing your real information needs
  • Step 2. More intelligent data – by creating relevant and meaningful performance indicators and qualitative management information linked back to your strategic information needs
  • Step 3. More intelligent insights – by using good evidence to test and prove ideas and by analyzing the data to gain robust and reliable insights
  • Step 4. More intelligent communication – by creating informative and engaging management information packs and dashboards that provide the essential information, packaged in an easy-to-read way
  • Step 5. More intelligent decision-making – by fostering an evidence-based culture of turning information into actionable knowledge and real decisions.

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As information and data volumes grow at explosive rates, the challenges of managing this information is turning into a losing battle for most companies. In the end they find themselves drowning in data while thirsting for insights. Combine this with an increasingly severe shortage of talent with analytics, data visualization and good communication skills, things look bleak for companies not adhering to lessons like those suggested in the Intelligent Company.

I get this stuff. In response to a quickening demand for knowledge and know how, I have developed training materials to address these decision-making challenges. The reason I founded DMAI in the first place was to empower more data-driven Decision-Making through the use of Analytics and business Intelligence. I’m happy to help you enable better decision-making in your business and turn it into an Intelligent Company.

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.

The “DMAI” in Risk & Compliance

When it comes to risk and compliance, the most successful teams are the ones who empower data-driven decision-making through the use of analytics and business intelligence. By bringing together the best talent, cutting edge technology and tried and true methodologies risk can be optimally mitigated and compliance best achieved.

The three primary skill sets I bring to the table are data-driven decision-making, analytics and business intelligence have served me well in both my risk and compliance work with Wells Fargo and in running my own business. Finding the right data at the right time is key to seeing potential issues before they arise, quickly solving them once they do, and putting the monitoring in place to make sure they don’t happen again.

Some of the risk and compliance successes I have achieved during my career include:

  • Managed project teams on a variety of analytics and compliance initiatives while providing guidance to less experienced consultants. This includes extensive anti-money laundering research and investigation data projects for bank remittances.
  • Identified compliance training opportunities and designed compliance training materials while with Wells Fargo Commercial Mortgage on various investment products.
  • Delivered extensive training on using big data and analytics to mitigate risk and follow compliance requirements across various financial services companies in the Philippines.
  • Have worked with a variety of internal and external resources during my 15 years with Wells Fargo to provide my expertise in analytics, risk management and compliance adherence.
  • Applied my process improvement knowledge (Lean Six Sigma) and data analysis expertise to develop corrective action plans and facilitate change with several departments of Wells Fargo and with dozens on clients in the Philippines.
  • Developed comprehensive reports and business dashboards using MS Excel, Tableau and Qlikview to deliver analysis to senior business leaders to influence the establishment of risk detection and mitigation controls. Relevant reporting topics from my time in Wells Fargo Card Services include anti-money laundering, remittance limit hits, high risk customer behavior, card services usage, competitor intelligence, household cross sell, and market penetration.
  • Worked closely with IT teams at various points in my career to develop security controls, risk monitoring tools, and QA reports to determine effectiveness of payment solutions with both Wells Fargo and within my own outsourcing business. I know how to code, I know how data is structured, and I know how data should be reported when it comes to risk & compliance.

10406025_10152524531307425_1404103117_nOverall, I have 20 plus years working in positions where managing risk and meeting compliance standards are part of the daily routine.

This has gifted me with an extensive knowledge and understanding of payment products like credit cards and remittances, fraud detection and prevention, and practical experience with risk monitoring and controls.

So from my perspective, Risk Management & Compliance needs to be neck deep in data-driven Decision-Making, Analytics and business Intelligence to be able to stay ahead of the game.

Analytics Consulting – DMAIPH specializes in a variety of analytics consulting solutions designed to empower analysts, managers and leaders with the tools needed for more data-driven decision-making. We have helped dozens of companies get more analytics in their business. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can tailor an analytics solution made just for your unique requirements.

Why Analytics Projects Fail: #4 – Lack of a Champion

A lot of time analytics project fail because there is no designated champion for the project.

I see a lot of money wasted on analytics technology because there is no one in the business who masters the technology. Who knows how to use it better than anyone else and knows what more can be done if other people become experts.

Good analysts are curious above all else. In the right place, they can do amazing things to drive innovation, increase profit, optimize processes and build market share. When you don’t have a a champion the outcome of any analytics project will be in doubt.

The most curious person in the organization should be the analytics champion because they love to go out and find the data to answer any business question that comes up.

If your analytics project doesn’t have a champion, then you most likely see a general lack of focus, an unclear vision and an uninterested leadership. Can you be that champion? If you think you can then do the Moneyball and Enchantment things from my last blog. They will help you gain your champion’s belt.

When you read Enchantment, you will start to understand that an analytics champion does as much influencing with their analysis as they do reporting.

Another way t5.5o be seen as the champion, is to make friends with people. Dropping off a box of donuts with the IT developers or sending thank you notes to project team members who went above and beyond is just as important as mastering the coding language used by your new analytics tools.

I keep a lot of analytics books on my desk. I make it obvious that I am always thinking about data and how to use it to improve what we do. I share a lot of content about analytics on social media. People know me as the data guy. You want to be like that if you want to be crowned Analytics Champion.

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.

Continued Growth in Data Analytics Outsourcing Market

http://www.datasciencecentral.com/profiles/blogs/analysts-forecast-continued-growth-in-data-analytics-outsourcing

Came across this interesting article and thought I’d share it…

The Trend of Outsourcing Data Analytics Activities

Over the past few years, businesses from all realms have come to accept the benefits of effective data analytics in understanding consumer choices properly and maximizing revenue potential. This has significantly boosted the demand for effective data analytics services in the global market.

However, not all organizations have the in-house knowledge, resources, and experience that it takes to analyze data effectively. What’s more, the resource pool of data analytics professionals has grown tight in the recent years, leading to a dearth of analysts who can develop competitively advantageous data insights. This has significantly boosted the global demand for effective data analytics services in the past few years.

The report on data analytics outsourcing market presents detailed insights about the major elements of the market and gives an overview of some of the factors that are impacting the market’s developmental prospects.

The data included in the report comes from a number of sources, including face-to-face and telephonic interviews, industry databases, and field observation data. Data pertaining to factors such as the primary concerns faced by the global data analytics market in the present scenario, the major growth drivers that are leveraging the market’s growth prospects, and the major trends that are defining consumer priorities in the market has been collected. The validity of the findings has been confirmed by cross-checking with multiple sources of information. The entire process of the research and development of the report also draws on the prior experience of researchers and inputs from industry experts.

I’ve sent up a couple of analytics team in the Philippines for clients in the U.S. and India. If you find yourself short on talent, resources and/or funding, I can help you get a team up in running in no time.

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