Analytics & Business Value – How Does Your Company Measure Up?

My son loves to fish. Taking pictures of the “big catch” is a great way to share his success with family and friends. But there is a trick to support the “story”. If you hold the fish as far in front of you as possible, the fish looks significantly bigger than its actual size.

What does this have to do with analytics and business value?

I often wonder when I hear someone talk about their successes in driving business value from analytics whether they are holding the fish a little farther out than reality. Ever have the same thought? The fact is that up until recently there was no industry benchmark associated with measuring the true value that companies are recognizing from their supply chain big data analytical efforts.

Well, that changed in 2017.

A team of professionals from Supply Chain Quarterly, the lharrington Group, the Universities of Arizona State and Colorado State along with Competitive Insights designed, issued, analyzed and published the results of the first global survey on this question. The goal was to have an objective benchmark for the progress that companies have actually made in deriving sustainable, actionable value from their big data analytical initiatives. In addition, barriers to success as well as future prioritized investments were captured. The results were organized by type of industry and demographics. Here is a link to the report published in the Q4, 2017 release of Supply Chain Quarterly.

We need your input?

Why? Simply said, the more companies that participate, the stronger the results. These results can be used internally to benchmark where you are compared to your peers and to gain an understanding of some of their challenges and priorities for future investment. It only takes a few minutes to complete and all responses are anonymous. Reporting is done by industry statistics and only those statistics are shared.

Look for the survey invitation from Supply Chain Quarterly in the coming weeks. Participate and help the results be of richer value for your company and the Supply Chain Industry. The results will allow you to see the reality of how you measure up.

All the best,

Richard Sharpe

Richard Sharpe is CEO of Competitive Insights, LLC (CI), a founding officer of the American Logistics Aid Network(ALAN) and designated by DC Velocityas a Rainmaker in the industry. For the last 25 years, Richard has been passionate about driving business value through the adoption of process and technology innovations. His current focus is to support CI’s mission to enable companies to gain maximum value through specific, precise and actionable insights across the organization for smarter growth. CI delivers Enterprise Profit Insights (EPI) solutions that enable cross-functional users to increase and protect profitability. Prior to his current role, Richard was President of CAPS Logistics, the forerunner of supply chain optimization. Richard is a frequent speaker at national conferences and leading academic institutions. His current focus is to challenge executives to improve their company’s competitive position by turning enterprise wide data from a liability to an asset through the use of applied business analytics.

Does your “Data Tank” Have Water In It?

It is hard to pick up any industry publication and not see articles on “the digitization of the supply chain” or “the value of supply chain visibility”, or “the power of analytics”. Certainly, the value of these types of supply chain advancements is significant. As certain, some companies will realize the value and thrive while others will not.

Is your operation ready to fully empower and utilize these advancements to get all of the true benefits that analytics can offer? Realized benefits that come from fact based, data driven decisions. Does your data have the high octane impact of TRUSTED data that you really need to run your business?

The Problem

Consider the impact on your business. Do data issues cause your organization to:

Be hampered by indecisive actions or bad decisions
Spend valuable time resolving data issues rather than solving problems
Experience organizational confusion and frustration
Have a lack of confidence and mistrust about specific functional data
Believe that data is more of a liability than an asset

You’re not alone. Data quality is a universal issue. A recent Harvard Business Review(https://hbr.org/2016/09/bad-data-costs-the-u-s-3-trillion-per-year) article states that data issues are costing businesses in excess of $3 trillion dollars a year in the U.S. alone! Here is a highlight from the article:

“The reason bad data costs so much is that decision makers, managers, knowledge workers, data scientists, and others must accommodate it in their everyday work. And doing so is both time-consuming and expensive. The data they need has plenty of errors, and in the face of a critical deadline, many individuals simply make corrections themselves to complete the task at hand.”

So what’s the impact of making less than optimal decisions because of imprecise, inaccurate, or untimely data for your company?

The Solution

Here are vital best practices to consider:

Create Executive Support – data issues create recurring and significant costs and are a real competitive risk. Quantify and qualify this impact to gain a C Level call to action.
Be Intentional – don’t try to “boil the ocean”. Focus on a critical business priority and demonstrate the value that having validated and trusted data has in the speed of the priority’s success.
Recognize The Power Of Cross-Functional Consensus – most decisions have a cross-functional impact. Involve other functions in the process to secure early buy-in to the solutions.
Apply Proven Methodologies and Technologies – don’t go after this by creating the solution from scratch. There are proven solutions to this problem that are timely, effective and repeatable.
Approach The Solution As Building Organizational Capability Not As A Project – operating system changes, acquisitions, changes in personnel are just a very few real world reasons that data issues are not a static set of problems. Solve your data issues by investing and building organizational capability to proactively address them over time.

More precise data leads to more precise information and ultimately superior knowledge. The wisest business person will make the worst decisions if they lack trusted, detail data.

There is more at stake than you might think. Companies that tackle their data issues and empower their decision makers with solid analytical capabilities will continue to win the competitive battle. Those that defer will disappear. Think Amazon!

Need ‘war stories’ and additional information to lead your company to better decisions through better data? Contact Tami Kitajima at [email protected] and we will be happy to provide that information.

All the best,

Richard Sharpe

The First Annual Supply Chain Data and Analytics Survey Results Are In – Where Do You Stand?

Have you wondered if other companies have the same level of difficulty and frustration regarding getting real and repeatable value from their supply chain data and analytical efforts? Well wonder no more. The results are in from the first global survey answering this question across multiple industries and they are significant.

Using Competitive Insights’ maturity model that is based on data organization & governance, cross functional utlilization and and the number of actual business analytics being routinely used, the current value being realized across all industries is 33.3% of the full potential value that can be derived from the effective use of supply chain analytics!

These results serve as a baseline for companies to have an unbiased source for measuring where they actually stand as it relates to other companies and industries. The survey provides findings that will be updated each year.

The results are published in the Q3 2017 issue of CSCMP’s Supply Chain Quarterly. The responses provide insights and answers to critical questions including:

What is the current satisfaction with the following four attributes of the data you need to do supply chain analytics?

What are the primary forms of technologies usedforyour supply chain analytics?

What types of analytics are your organization taking the most advantage of?

What are the most significant barriers that you have in getting more value?

What benefits have you realized to date from your supply chain analytical investments?

Want to know more? If you already subscribe to Supply Chain Quarterly, then the answers are on the way. If not, you can read the article HERE.

Once you review this information, use it to drive your own internal discussions. Measure your results against other companies. Learn how you might take actions to obtain the maximum value out of your supply chain analytical investments! And just as important SIGN UP NOW to participate in next year’s survey!

All the best,

Richard

Taming the Big Data “Monster” – A CSCMP Learning Opportunity

Are you attending CSCMP’s 2017 Edge Conference in Atlanta next week? Would you like to know where your company stacks up with regard to other companies’ success in deriving real and sustainable financial value from Big Data and Analytics investments?

Please join us at 10:30 am on Monday morning (Track 16) to hear the results of a global survey conducted by CSCMP’s Supply Chain Quarterly, Arizona State University, Colorado State University, the lharrington group and Competitive Insights titled Taming the Big Data “Monster”.

The session will provide meaningful survey insights on the true challenges and benefits that companies have experienced as well as their expectations for future big data and analytics investments. This survey will be continued yearly and will be a valuable resource to measure the progress companies are making in applying big data analytics to support increases in profitable performance . This year’s inaugural release will serve as a starting point for your company to measure and track the progress that you are making versus other companies. At the session you will want to sign up to receive a copy of the full report.

Seats will be limited so please come early and join us on Monday, September 25th from 10:30 – 11:45 a.m. (Level 2 C211-C212) to learn more.

All the best,

Richard

Baselining Your Realized Value and Learning From Other Companies

Gartner estimates that companies will spend $18.3 Billion on analytics and big data initiatives in 2017, an increase of 7% over 2016. That number is expected to grow to $22.8 Billion by 2020 as executives are becoming more cognizant of the importance of gaining sustainable value from big data analytical capabilities. Earlier this year Dun & Bradstreet and Forbes Insights explored this question through a survey of over 300 executives across multiple industries and regions. Here is a link to a recently released report sponsored by Dun & Bradstreet summarizing the results that is well worth the read.

How much has your company spent (internally and externally) over the last 18 months on analytics and big data initiatives? What are your Executive Team’s expectations of ROI? Have you come anywhere near meeting these expectations?

As I mentioned in my last posting, we hear two very different responses when talking with companies about their success in mastering growing volumes of supply chain data and gaining sustainable value from business user analytics. The first is a public ally declared answer of success and progress while the second one, once the door is shut, typically offers various degrees of frustration and minimal progress. To understand the real progress of other companies’ big data analytical efforts, you need a non-speculative way to measure your progress versus your peer companies. You need the ability to have a better understanding of peer companies’ challenges, the benefits they have realized, and their focus for future analytics and big data investments.

I am pleased to announce that the global survey conducted by a team comprised of CSCMP’s Supply Chain Quarterly, Arizona State University, Colorado State University, Competitive Insights LLC, and lharrington group LLC has successfully captured the information required to establish this supply chain industry baseline for big data analytics. The outcome of this survey supports the identification of true challenges and benefits that companies have experienced as well as what they expect to gain from future big data analytics investments. These results serve as a starting point to measure and track each year the progress that companies have made in realizing the value from big data analytics. This year’s survey results will be presented at the annual Council of Supply Chain Management Professionals (CSCMP) Conference and published in various articles in both the CSCMP’s Supply Chain Quarterly and DC Velocity.

So when the door is shut and you are having internal discussions on your successes and frustrations in deriving value from your big data analytics investments, you now have a way to move from speculation to fact.

Where are other companies breaking through the challenges ot rapidly accessing the right data, in solving quality and timing issues and their ability to continually gain meaningful analytical answers to prioritized business problems?

What are their next set of prioritized areas of focus?

One interesting early discovery from the survey results is that some technologies used for big data analytics do offer limited benefits but fall short in providing the true overall business value that can be gained from successful analytical efforts.

Naturally, this surveying effort will only get stronger as we learn from you what is beneficial and what is needed to get more insightful information. If you did not participate this year, please take the time to complete next year’s survey. It will only take a few minutes but the impact can be significant. Participants of this year’s survey represent over 20 industries around the world.

This year’s results are clearly statistically sound. Lets make next years participation a blowout!

All the best,

Richard

Where Are You Really In Taming The Big Data and Analytics Monster?

There are often two answers that I hear when talking to companies about where they are in mastering growing volumes of supply chain data and gaining sustainable value using various forms of business user analytics.

The first response is the one publically offered – “We have made substantial investments in technology and expertise and are well on our way in harnessing real value from our data.”

The second “real” answer, once the door has been shut and confidentiallty agreements have been signed, is one of frustration and disappointment. “Our progress has been extremely slow. Yes, we are doing the traditional project exercises like various forms of modeling. However, it is still difficult to get to the value-added information directly into the hands of the decision makers quickly and consistently for ongoing strategic and tactical needs. Even if they do get this information, there is often an underlying doubt about the quality of the data used in generating the required information.”

Companies need to have a measure of how they stack up against other organizations in their journey to master big data and analytics. To address this need, a survey has been created by a team from Arizona State University, Colorado State University, Competitive Insights, CSCMP’s Supply Chain Quarterly and the lharrington group LLC. The purpose of the survey is to capture meaningful answers regarding the progress that companies are making in mastering data and the application of meaningful business analytics. The result will be used to create a Supply Chain Industry Baseline that reflects meaningful responses from a multitude of companies, different industry segments and regions of the world.

This survey will be issued on an annual basis to serve as a means to track the progress that companies are making year over year. The comparisons will show where and how companies have been successful. Finally, it will be a resource to understand the actual challenges and frustrations being experienced by companies in their pursuit to master their data and meaningful business analytics. Therefore, the survey findings will be a resource for companies to determine how their efforts measure up to other companies and to serve as input for internal discussion on big data and analytical priorities.

A preview of this year’s findings will be issued, prior to general release, to all of those that respond to the survey. Highlights of the findings will be presented and discussed at the annual Council of Supply Chain Management Professionals (CSCMP) Conference in September. More detailed results as well as other relevant research will also be published in the Supply Chain Quarterly and DC Velocity.

Over the next following weeks, recipients of Supply Chain Quarterly, DC Velocity and Competitive Insights‘ monthly newsletter will be receiving this electronic survey that has been carefully designed to create this industry Baseline. Responses will only be used to create the Baseline and the associated correlations and findings. No individual response will be published or referenced in the results or used for any company solicitation.

The more companies that respond and the more honest their responses, the stronger the results will be for EVERYONE in the Supply Chain Industry. Please take the survey HERE or at colostate.az1.qualtrics.com/jfe/form/SV_bO98R0OrXZTnxYN

All the best,

Richard

The problem is the data

“Harnessing the true power of data driven insight is the holy grail of future business. A wealth of this data comes from the supply chain. But, while the information is there, companies are not yet capitalizing on its real value as a source of insight capable of shaping the future of the enterprise.”

—DHL Supply Chain, Lisa Harrington, Senior Research Fellow – University of Maryland,
“The Predictive Enterprise: Where Data Science Meets Supply Chain”  (January 2016)

With all of the talk about analytics and big data, why are so many companies still struggling with the adoption of new technologies and methodologies that harness the true power of data-driven insights?

The reasons can vary, but the common complaint that I hear centers on data:

Our data still sits in silos and it is difficult to integrate.

We have pulled all our data together, but people still don’t trust it.

As a large company, we have a long way to go to be able to support advanced analytics with the current state of our data.

Does this resonate with you for your company? If so, doing nothing to move down the path to gain this Holy Grail is nonsensical.

This problem has been solved by many forward-thinking companies using advances in cloud computing solutions and focused methodologies. They took on the challenge and solved this “secret” to gain significant operating advantages.

Take a look at the ROI figures from a recent Gartner research report, “Deconstructing Supply Chain Analytics,” by Noha Tohamy (also referenced in the DHL paper mentioned above).

After reviewing the ROI, make an honest assessment about your organization’s capability to use the power of analytics that exist today. Consider the competitive advantage of having one source of trusted data and the full use of business-focused analytics to transform your enterprise.

If your problem centers on the state of your data, what is more important than to eliminate that barrier? The task may be significant, but it starts by recognizing that it can be done. Seek the support of your Senior Management to create a cross-functional Team charged with defining a road map that includes an ongoing data-governance process. If needed, seek outside assistance to help with the process. You will discover that it is not so much rocket science as it is perseverance!

I would love to hear your thoughts.

All the best,

Richard

Roadkill – How To Avoid Being Crushed By Data

Imagine that you are having a dream that is quickly turning into a nightmare. You find yourself standing in the middle of a newly constructed super highway. You are amazed at the vast number of lanes on both sides of this man made structure. You have been told that you are there to find out how drivers are performing on these lanes with accurate measurements and to report back meaningful insights. To do this, you are to utilize your computer, camera and a smart phone.

As you stand there trying to get your bearings, you notice the following:

the volume of the cars moving in each direction is significantly increasing over time
cars are entering from a variety of new entry points
the speed of the cars is exponentially increasing to a point that what you are seeing is turning into a blur

You feel helpless using the tools that you have been given and cannot see how to possibly do your job. In fact, you realize that if you are not careful, you could become so confused that you could put yourself in harms way and become a roadkill casualty!

Sound silly? I am sure it does but replace the road lanes with data streams coming from a growing number of sources and at an ever increasing rate of speed. Add the pressure of a rapidly changing commercial environment and the need to gain meaningful insights to stay ahead of the competition or to be left behind in the commercial dust. It is not too much of a stretch of the imagination.

Recently, I watched an interview of Thomas Malone, from the MIT Sloan School of Management on DCV-TV. The interview concerned his prediction 25 years ago on the emerging role of e-commerce.

Mr. Malone made several interesting observations about how successful organizations will operate and win using ever increasing amounts of data:

by harnessing the power a collaborative approach between man & machine where both contribute and learn from the work of the other (“collective intelligence”)
by creating an environment to empower the individual to use data and computing power to solve critical business needs (e.g. Google and eBay)

These are directly applicable to any company’s strategy in getting the full benefit of the ever increasing volume and speed of data and to obtain a competitive advantage over your competition.

Let’s build on Mr. Malone’s thoughts and go back to our analogy of not being “roadkill” on your data super highway. How many of the following are true for your organization?

You have cross-functional consensus on the value of measuring specific areas of performance
You have a technology platform provides one “One Version of the Truth” of information captured from ever increasing sources and volumes of data
You have created a user environment that empowers individuals to continually gain insights by applying their creative skills in addition to taking advantage of advanced computing correlations and learnings (“collective intelligence”)
You have recognized that your approach must be scalable and repeatable for sustained value
You periodically highlight to the organization the value that has been gained by the effort

The world today is full of examples where relatively young companies are outpacing traditional competitors in multiple industries by changing the game of how to win market share.

I read recently that certain state Department of Transportation organizations are experimenting with recycling roadkill into compost as a cost savings initiative (click here for article).

Companies that take on the challenge of mastering their data and empowering individuals with various forms of intelligent analytics will not need to worry about being someone else’s compost. For everyone else, there are no guarantees. Like Mr. Malone said, just look at Google and eBay!

I would appreciate hearing your thoughts and comments.

All the best, Richard

Turning Big Data From A Liability To An Asset – Point 4: Creating Repeatable and Measurable Impact

This posting is the final in a series focused on turning Big Data from a liability to an asset. Earlier in the series, I have discussed the importance of gaining Organizational Consensus, Taking An Enterprise Wide Approach and the need to have effective Data Governance in addressing effective ways to get value from your Big Data initiative. I hope these areas of focus have been helpful. Today, we will focus on Creating Repeatable and Measurable Impact.

To effectively tackle Big Data, the strategy must be intentional with regard to the business need that the effort will support. All too often I hear someone suggest that the way to address Big Data is to hire a few very smart data scientist, put them in a room with access to enormous amounts of data and see what they can discover. I totally disagree with this approach. Sure, they may find interesting business patterns or correlations but deriving financial value from the effort may be difficult. Instead, a far better strategy is to focus your Big Data initiative on a specific business strategy(s) where the insights gained from Big Data can be used to make actionable decisions that can be tracked with regard to a measurable improvement in the business meeting its objectives.

Tackling Big Data requires the investment of time and resources. Like any business investment, the initial justification for tackling Big Data needs to be financially justified, but getting value from Big Data in an intentional way is not a one-time event. It needs to continue to provide value that can be measured in meaningful ways to the organization. Without that, it is purely a waste in time.

So the question is how. Measuring value can be a tricky task but it cannot be ignored and pushed out to be addressed “after the fact”. Like any measurement, the first step is to verify you have a Baseline “value” for performance that should be defined and cross functionally agreed upon. It is also important that the way you calculate the measurement has been scrutinized and validated, so that it will not be questioned later by the “Doubting Thomas” members of your organization. All of this should be done prior to taking action that is directly linked to the insights you gained from your Big Data initiative. Finally, it is key that the ongoing use of the measurement of value is consistently applied each time it is used.

These are all standard value measurement considerations but they are just as important for sustaining your Big Data initiative as they are for any other business investment.

We would appreciate hearing your thoughts and comments. All the best, Richard

Turning Big Data From A Liability To An Asset – Point 3: Data Governance

Big Data is something that companies are trying to define with regard to what it means to their operation and to their competitive landscape. When considering the growing number of sources of unstructured data (e.g. social media) and structured data, just defining the landscape of what you are talking about can be difficult. In this blog we have provided a framework for how to define Big Data, getting value from Big Data and now providing actionable points on how to turn a three headed monster into something that adds significant and ongoing business value.

In an earlier posting we identified the requirement to gain cross functional consensus with regard to how Big Data solutions are created to serve the intended purpose of solving a business problem(s). We also focused on why it is so important to take an enterprise wide perspective to maximize the value of the investment. In this posting, we will focus on the importance of data governance.

What does data governance have to do with Big Data? Everything. Effective solutions take time and resources to build correctly. The question is do you want that investment to solve a business problem one time or to continue to support solving the business problem over time.

Problems are solved by business leaders and managers making decisions that positively impact the efficiency and financial impact of the operation. Decisions that are fact based and that are actionable.

Ok, so what does that have to do with Data Governance? Let’s say that you have a significant business problem to solve. The information that you have in front of you is known to be consistently accurate and specific to the problem area. This is a function of the information coming from the same source, that the information has been verified by Subject Matter Experts (SMEs) and the way that it has been processed is consistent to provide the information you need. What did I just describe? Data Governance; the insurance policy for Big Data, and this insurance policy continues to provide returns as you measure the impact of those decisions over time.

Data Governance provides the rules for which you are obtaining, organizing, validating and processing the vast amounts of structured and unstructured data to gain competitive advantage. Without it, your Big Data investments are a waste of time.

We would appreciate hearing your thoughts and comments. All the best, Richard

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