Month: May 2016

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.

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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.

I Would Add Good Data & Analytics …

I came across this picture awhile back … For anyone who consistently challenges themselves, they can relate to most of these points.

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  • Persistence
  • Failure
  • Sacrifice
  • Disappointment
  • Dedication
  • Hard Work
  • Good Habits

And to this list I will add two more:

  • Good Data
  • Analytics

One thing I think we do not do enough of in both personal and business decision-making is to find ways to track the effectiveness of being persistent. Knowing when to stay the course, go in reverse or take a quick turn to the left can guided by tracking the success behind being persistent.

Likewise, having a measurement for failure vs. success can be important too. In sports we look at failure rates all the time.. .a .200 hitter or a 25% shooter is a failure. So its much easier to know if you are good at hitting a ball or making a basket when you have measurements.

Sacrifice and disappointment are a bit trickier to quantify, but we can still come up with ways to measure these too through tools like a self-assessment or survey.

Dedication, hard work and good habits can also be challenging to tie a metric too a first. But if you come up with formulas that take production, quality and consistent data and combine them you can come up with something workable.

Infusing some data and analytics into how you judge your success will go a long way in helping you maintain that level of success.

Good data is pieces of information or knowledge that can be used in measuring success. How do you know if you are successful unless you have something to compare your data too.

Analytics allows you to use the data for analysis to understand how you got to be a success and what factors might cause you to lose that success.

Curious about how to put some more data and analytics into your business. so you can have a better idea of what success is supposed to look like? I’m here to help.

 

 

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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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.

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.

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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.

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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.