Data Governance and Fruitcake

S&OP with Profit
tackle supply chain stress

Data Governance and Fruitcake

data governance and fruitcake

“Bad data is the fruitcake nobody eats.” Fruitcake gets put in the corner. Nobody serves it. Everybody hates fruitcake and everybody hates dirty data. As SteveMo shares, “At least fruitcake is good for re-gifting. You can’t re-gift dirty data.”

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.

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

How to Implement Supply Chain Value Adding Analytics – Cross-Functional Data Validation

S&OP with Profit
tackle supply chain stress

How to Implement Supply Chain Value Adding Analytics – Cross-Functional Data Validation

transportation

“Using siloed data is the Achilles heal for identifying actionable insights to reduce costs and protect profit margins. With today’s extreme inflationary pressures coupled with limited resources and product shortages, it is critical to have cross functional participation in creating “one version of the truth” to stop information disconnects and to rapidly drive actionable decisions."

-A Supply Chain Industry Forum

In order for any analytical solution to be meaningful, the issue of data quality needs to be addressed. The goal is to demystify the whole notion of harnessing Big Data analytics from being a seemingly impossible, daunting task to one of creating an invaluable asset that drives significant financial performance improvements.

Case Study

While I was the President of CAPS Logistics for over 8 years, the company serviced over 16% of the Fortune 500 in various forms of supply chain decision support applications. These efforts spanned the globe from supporting the expansion efforts of a worldwide soft drink company, to the redesign of supply chain networks for multiple CPG and specialty manufacturing companies and providing different transportation solutions to one of the largest companies in the waste management industry. The technology was proven, the people were bright and the focus was to provide the best solutions possible. Unfortunately, in most cases, the implementation of these carefully engineered solutions was either slowed down or even put on hold. Why? Other departments would offer objections often citing concerns about the “quality” of data used for the analysis. Typically, the nail in the coffin would be that if they would offer that their data concerns were correct, the integrity of the solution could cause the company to miss its revenue targets. Sound familiar? The end result was that the company did not attain the competitive advantage that was possible.

Let’s take this lesson to the world we live in today

In a world of exponentially growing data associated with the operation of your enterprise the problem sited above had two issues. The “quality” concern which will be addressed in a future posting on data governance. The second issue was not having cross-functional consensus. In the projects mentioned above, efforts were made to involve other departments at every stage of the project but gaining supply chain efficiencies were not their highest priority. Therefore, these other functional groups had no real buy-in in the work effort.

If you believe that Big Data has the opportunity to drive significantly recurring financial improvements, then the table stakes are even higher with regard to early organizational buy-in. Buy-in with regard to getting everyone on the same page on how to repurpose and use Big Data to empower multiple forms of new analytical and strategy development capabilities. I am guessing that many of you are saying “yea, right for our company; this would be comparable to building Noah’s Ark.” You may be right but it is a challenge that deserves careful consideration as offered by the following quote by Benjamin Franklin:

Benjamin Franklin

“By failing to prepare,
you are preparing to fail.”


Success will also require having the right level of Executive sponsorship and taking advantage of the power of cloud technologies and proven methodologies. In addition, other key points need to be integrated into your approach including obtaining cross functional consensus on any data issues. If this is not a mandate, you run the serious risk that organizational questions will surface which can stop the entire effort.

So why go to the effort?

Isn’t the political risk too significant and the task too big to undertake now especially given all of the mission critical projects that are already established for the company? That might be the right answer but let’s look at it another way. Is it possible that your Board and certain members of your Executive Team are wondering if the company will be left behind when your competitors harness the value of Big Data? Value that is measured by increasing financial performance and competitive advantage. Only you know the answer to that question, but if the decision is made to take the first move advantage, be sure the process you use requires cross functional organizational consensus as a cornerstone of the solution.

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

Thriving After COVID – Essential Step 1 – Data

Richard Sharpe Analytics & Big Data

Thriving After COVID – Essential Step 1 - Data

solutions exist that can validate and transform transactional data into actionable insights quickly and efficiently

overcoming data challenges

Summary

How is your company working through the impact of COVID-19? How are you deciding what products to sell and what should be eliminated? How are you deciding the priority of applying your Supply Chain Risk Management resources to your most important suppliers?

Is the driving criteria for these decisions the same type of financial measurements used pre-COVID? Standard financial measurements that do not tell you what small percentage of your customers and products are actually driving the vast majority of your profits and net cash flow?

This is the time for the smartly re-tooling of your business based on profit contributions by customer, product and channel. Re-tooling that breaks away from the “Herd Mentality” that your competitors are pursuing?

But how do you get there? What are the roadblocks that come to mind?

Roadblock 1: Data

A popular and profitable apparel company wanted to better understand the profit contributions for every product, customer and channel. They had tried to do this analysis internally and failed. At the urging of their new EVP of Global Supply Chain a subsequent meeting was held with their CFO.

Mike walked up to the projector screen to see the actual cost and profit details by product and customer and said:

“I just don’t think our data is good enough to provide this type of analysis. It is fragmented and inconsistent. I do not trust it enough to deliver these types of results.” - CFO of a leading Apparel Company


bridge

4 months later …. $25 Million Opportunity To Reduce Inventory Working Capital

Today, solutions exist that can validate and transform transactional data into actionable insights quickly and efficiently. Companies that move from the crutch of data limitations to addressing data as a significant asset will be the ones that are crossing the bridge to have sustainable profit margin contributions. Actionable data that is specific, accurate, trusted and repeatable.

Please comment on this posting or email me at [email protected] .

All the best,

Richard Sharpe

Richard Sharpe

Richard Sharpe is CEO of Competitive Insights, LLC (CI), a profit contribution analytics firm that specializes in helping clients efficiently and continuously transform multiple sources of data into actionable operational insights.

Best Practice Bridge

Global Analytics Survey – Recognition, Frustration & Best Practices

Richard Sharpe Analytics & Big Data

Global Analytics Survey – Recognition, Frustration & Best Practices

Recognition

For three years, Competitive Insights has had the privilege to help orchestrate the Annual Analytics & Big Data Benchmark Study published in Supply Chain Quarterly and DC Velocity each year. As in past years, the responses from the participating companies indicate that most feel that they are early in their journey in achieving that full potential that is possible form Big Data Analytics as demonstrated below:

Big Data Maturity

 

Frustration

So what is holding companies back from realizing the full value that can be derived from the sustainable use of Big Data Analytics? Frustration for achieving success can be associated with people, processes, technologies and data related issues. The complete results of the survey is available by request.

Big Data Impediments

Action

How can companies accelerate their progress and get the most value from their Big Data Analytical initiatives? We endorse a “Crawl, Walk, Run” as a bridge to move from a state of frustration to one of ongoing success.

Best Practice Bridge
 

The following is offered as a quick checklist of best practices that we have seen work throughout the years.

Address the People Considerations

Bridge - People

People

  • Involve other functions early on
  • Avoid “one-off” single design efforts
  • Link value to key initiatives
  • Ensure visibility of Senior Levels

 

Consider the Best Process for Development

Bridge - Process

Process

  • Share success with other functions
  • Be intentional with your focus
  • Adopt a crawl, walk, run approach
  • Measure the direct financial impact

 

Use Focused Technology Techniques

Bridge - Technology

Technology

  • Design for business users (cross-functionally)
  • Apply Agile development techniques
  • Ensure scalability

 
 

Turn Data From a Liability to an Asset

Bridge - Data

Data

  • Gain organizational consensus on enterprise data sources (cross-functionally)
  • Focus the data design (not boil the ocean)
  • Invest in repeatable data validation capabilities (organizational trust)

 

Companies recognize that actionable knowledge that comes from Big Data Analytics is key for survival. Knowledge that allows for informed strategies and decisions that are fact based. Strategies that drive positive and meaningful results. Decisions that allows the organization to out maneuver the competition. Survival will go to those that accurately understand operational performance and the associated drivers.

I would love to know your thoughts on this.  Please comment on this posting or email me at [email protected] .

All the best,

Richard Sharpe

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.

Digitizing The Supply Chain – Maximize The Value

Richard Sharpe Analytics & Big Data

Digitizing The Supply Chain – Maximize The Value

digitizing the supply chain

Summary: A lot is being written about companies recognizing the need to “digitize” their supply chain.  But what does that really mean?  Generically, digitization is to convert information into a digital format.  But in the context of supply chain, let me offer the following:

Digitizing the supply chain is to meaningfully connect and make available data associated with the Plan, Source, Make, Deliver and Return (SCOR) functions of the supply chain.

In other words, having repeatable and trusted digital visibility of the end to end supply chain.  This information can then support:

  • the proactive monitoring of product flows (Control Towers)
  • improvements in operational efficiencies (S&OP applications) or
  • critical insights regarding the total actual cost to serve for each product and customer

Why is this a topic that is top of mind for many supply chain executives?  Is it correlated to serving customers better, driving efficiencies, lower costs or beating the competition and therefore driving profitable growth?  Absolutely!

But achieving these objectives and maximizing value is not only an investment in digitization.  Achieving real value requires breaking down the organizational silos using this information to gain maximum advantage;  investments in the people and processes as well as the technologies.

Case In Point:  I was recently interviewed by Supply Chain Radio Now  and told the story about a major Waste Disposal company. The company wanted to use digital supply chain operational data to better plan and execute servicing their residential customers on a national basis.  They had selected our company’s technology but the CFO sponsor had a traditional, technology focused strategy for it’s deployment.  We explained to the CFO that his deployment strategy would not work because it did not address the required attention needed to address the process and people related requirements.

Action:  The CFO took the position that if his deployment strategy was not used, the business (worth several million dollars) would be given to another company.  We respectfully but clearly explained our position and he left the building.  The next day, he returned and said that he had changed his mind because of our conviction in the proper deployment strategy.  The subsequent adoption of the solution was extremely successful and led to additional national solution rollouts for the same company.

Takeaway:  Digital visibility that provides connected, trusted and actionable end to end supply chain information is one key for “thriving” and not just “surviving”.  But it also requires addressing the people and process considerations in order to take full advantage of the information across the organization.

Mastering the digital supply chain will separate the winners from the losers.  It can support multiple critical needs including knowing the exact financial contribution of every product or service sold to every customer. That type of insightful knowledge can make servicing my trash can and yours an even more profitable venture.

I would love to know your thoughts on this.  Please comment on this posting or email me at [email protected] .

 

All the best,

Richard Sharpe

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.

Don’t Use Data Integrity Issues As A Crutch

Richard Sharpe Analytics & Big Data

Don’t Use Data Integrity Issues As A Crutch

transportation

Summary: “Our data has significant challenges and this is a real handicap for us.”  It is rare to talk to a company that believes they have very little challenges with their data.  In fact, the recent Supply Chain Quarterly Big Data Analytics Survey found that data quality and access issues were one of the main frustrations that business users have in getting true business value from their analytical initiatives. Unfortunately, many companies use their data liability issues as a crutch to justify why they are not getting true value of business analytics.

Case In Point: Several years back, a meeting was being held with the CFO, COO and SVP of Supply Chain for a well-known apparel company.  They knew that they needed to build the analytical capabilities of their organization but were skeptical because of their perception of the current state of their data. Fortunately, the SVP of Supply Chain had previous experience in tackling this issue.  He convinced the others to take a first step that would demonstrate that their data could be turned from a liability to an asset to produce meaningful insights on opportunities to reduce costs and increase profit margins.

Action: A Project Team was assembled and all sources for their transactional data associated with their supply chain and sales operations were identified. Data Subject Matter Experts were involved to address any data issues. Consensus was reached by the Team on how the data should be intentionally transformed to build a foundation for SKU and customer specific cost and profit performance information. Cloud-based technology was then used to further validate the data and to create specific and actionable financial performance insights that could be refreshed periodically. By benchmarking performance of similar customers and products, significant financial opportunities were identified. The Project team also found an unexpected bonus associated with potential inventory working capital reductions in excess of $10 million dollars.

Takeaway:  Competitive Insights presented at the CSCMP Global Conference in November of this year.  As part of that presentation, recommendations were made on basic building blocks to address data issues. You can receive a copy of this presentation at this website.

Data integrity issues can be proactively handled to ensure that operating data becomes a valuable asset.  An asset that allows for visibility into actionable insights that drive trusted, fact based decisions. The companies that take this seriously will consistently move ahead of their competition and drive additional profitable performance.,/h3>

I would love to know your thoughts on this.  Please comment on this posting or email me at [email protected] .

 

All the best,

Richard Sharpe

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.

Global Survey Results – Recognition, Frustration & Action

Richard Sharpe Analytics & Big Data

Global Survey Results – Recognition, Frustration & Action

The results are in.  At this year’s CSCMP Global Conference in Nashville, the Team of professionals that conduct, analyze and report on the Annual Analytics & Big Data Benchmark Study (Lisa Harrington – lharrington group LLC, Susan Lacefield – Supply Chain Quarterly, Dale Rogers – Arizona State University, Zac Rogers – Colorado State University and myself) presented the findings of this year’s survey (a copy of the presentation can be made available – see below).  The results clearly indicated that companies continue to recognize the need to gain business value from Big Data Analytics but that there is a significant amount of frustration across industries.

Challenges with data, struggling with meaningful analytics and ultimately getting to actionable strategies were clear drivers for this frustration.  As an example, look at the attached graphic on data:

image from www.ci-advantage.com

The good news is that companies are gaining a deeper appreciation for the business value that can be derived from Big Data Analytics and are being more objective with regard to the effort that is needed to achieve that value.  So what are some key steps to cross that gap faster?  Four primary areas and specific actionable steps were cited to drive success as depicted in the following graphic:

image from www.ci-advantage.com

So the race is on.  Companies get the fact that in the fast paced environment that we all operate in today, it is critical to make fact based decisions using the all of the transactional data that is available through a set of business user analytics. Decisions that drive competitive and profitable performance.

For a copy of the presentation, please contact us at [email protected]

Thank you,

Richard Sharpe

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.

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

Richard Sharpe Analytics & Big Data

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

Blog037_KidFishing
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

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?

Richard Sharpe Analytics & Big Data

Does your “Data Tank” Have Water In It?

Blog037_GasCarRoad
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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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

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.

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

Richard Sharpe Analytics & Big Data

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

Blog35_wave
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:

  1. What is the current satisfaction with the following four attributes of the data you need to do supply chain analytics?
  1. What are the primary forms of technologies usedforyour supply chain analytics?
  1. What types of analytics are your organization taking the most advantage of?
  1. What are the most significant barriers that you have in getting more value?
  1. 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

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.