Data Driven Supply Chain Analytics Tools Are Not Enough

Supply Chain Analytics practitioners can learn a lot from Customer Analytics. The two domains are based on similar business fundamentals. What we find is that data and data-driven decision tools are not enough. The biggest difficulties in supply chain or Customer Analytics lie in the cultural practices of organizations.

The following article was written by Maz Iqbal who provided his valuable perspective from a Customer Analytics point of view.

On LinkedIn, Don Peppers is sharing his perspective on making better decisions with data. This got me thinking and I want to share with you what showed up for me. Why listen to my speaking? I do have a scientific background (BSc Applied Physics). I qualified as a chartered accountant and was involved in producing all kinds of reports for managers and saw what they did or did not do with them. More recently, I was the head of a data mining and predictive analytics practice. Let’s start.

Data and data driven decision-making tools are not enough

Yes, there is a data deluge, and this deluge is becoming down faster and faster. Big enough and fast enough to be given the catchy name Big Data. What is forgotten is the effort that it takes to get this data fit for the purpose of modeling. This is no easy-cheap task. Yet, it can be done if you throw enough resources at it.

Yes, there are all kinds of tools for finding patterns in this data. And in the hands of the right people (statistically trained-minded, business savvy) these tools can be used to turn data into valuable (actionable) insight.

This is not as easy as it sounds. Why? Because there is shortage of these statistically trained and minded people: amateurs will not do, experts are necessary to distinguish between gold and fools gold – given enough data you can find just about any pattern. It statistical savvy is not enough you have to couple it with business savvy. Nonetheless, let’s assume that we can overcome this constraint.

The real challenge in generating data driven decision-making in businesses is the cultural practices. We do not have the cultural practices that create the space for data driven decision-making to show up and flourish. A thinker much smarter-wiser than me has already shared his wisdom, I invite you to listen:

"On the whole, scientific methods are at least as important as any other research: for it is upon the insight into the method that the scientific spirit depends: and if these methods are lost, then all the results of science could not prevent a renewed triumph of superstition and nonsense. Clever people may learn as much as they wish of the results of science – still one will always notice in their conversation, and especially in their hypotheses, that they lack the scientific spirit; they do not have the distinctive mistrust of the aberrations of thought which through long training are deeply rooted in the soul of every scientific person. They are content to find any hypothesis at all concerning some matter; then they are all fire and for it and think that is enough …….. If something is unexplained, the grow hot over the first notion that comes into their heads and looks like an explanation…."

- Nietzsche (Human, All Too Human)

It occurs to me that the scientific method never took route in organizational life. Put aside the rationalist ideology and take a good look at what goes in business including how decisions are made. I say you will find that Nietzsche penetrating insight into the human condition as true today as when he spoke it. The practice of making decisions in every organization that I have ever come in contact with is not scientific: it does not follow the scientific method.

On the contrary, managers make decisions that are in alignment with their intuition, their prejudices, and their self-interest.  It is so rare to come across a manager (and organization) that makes decisions using the scientific method that when this does occur I am stopped in my tracks. It is the same kind of unexpectedness as seeing a female streaker running across the football pitch in a league match.

What are the challenges in putting data driven decision-making practices into place in organizations?

Technologists have a gift. What gift? The gift of not understanding, deeply enough, the being of human beings. Lacking this understanding they can and do (confidently) stand up and preach the virtues-benefits of technology. If life were that simple.

Truth shows up as attractive to those of us who do not have to face the consequences of truth. Data driven decision-making sounds great for those of us selling (making a living and hoping to get rich) data driven tools and services.

The challenge of putting in place data driven decision-making practices is that it disturbs the status quo. When you disturb the status quo you go up against the powerful who benefit from that status quo. Remember Socrates:

"The very nature of what Socrates did made him a disruptive and subversive influence. He was teaching people to question everything, and he was exposing the ignorance of individuals in power and authority. He became much loved but also much hated …. In the end the authorities arrested him for …., and not believing in the gods of the city. He was tried and condemned to die…"

- Bryan Magee, Professor

 

Beware of being successful in putting in place a culture of data driven decision making!

With sufficient commitment and investment you can put in place a data driven decision making culture. Like the folks at Tesco did. And by making decisions through harnessing the data on your customers, your stores, your products, you can outdo all of your competitors, grow like crazy and make bumper profits. Again, again, and again. Then the day of reckoning comes – when you come face to face with the flaws of making decisions solely on the basis of data.

Tesco is not doing so great. It has not been doing so great for several years – including issuing its first ever profits alert in 2012. What is the latest situation?Tesco has reported a 23.5% drop in profits in the first half of this year. What has Tesco been doing to deal with the situation? This is what the article says:

Last year, Tesco announced it would be spending £1bn on improving its stores in the UK,investing in shop upgrades, product ranges, more staff, as well as its online offering.

There are a number of flaws on data driven decision making. For one data driven decision making assumes that the future will be a continuation of the past. Which is rather like saying all the swans that we have come across are white, so we should plan for white swans. And then, one day you find that the black swan shows up! The recession and the shift in consumer behavior that resulted from this recession was the black swan for Tesco.

Furthermore, I hazard a guess that in their adoration at the pulpit of data driven decision making the folks at Tesco forgot the dimensions that matter but were not fed into the data and the predictive models. What dimensions? Like the customer’s experience of shopping at Tesco stores: not enough staff, unhappy staff, stores looking more and more dated by the day, the quality of their products...

It looks like the folks at Tesco did not heed the sage words of one of my idols:

Not everything that counts can be counted, and not everything that can be counted counts.

– Einstein

This article on ‘Musings on Big Data, Customer Analytics, and Data Driven Business‘ was written by Maz Iqbal who is an expert committed to helping executives, teams and organizations to do well by creating superior value for customers and enriching the lives of all stakeholders. His website is http://thecustomerblog.co.uk/

Most Important Supply Chain Analytics Skills

The demand for data analysis skills by supply chain organizations is growing. What are the most important skills needed for performing effective supply chain analytics? “In addition to the technical skills required, supply chain analytics practitioners and supply chain consultants need deep domain knowledge in the industry as well as excellent communication skills.

Business Analytics Among IT Skills Expected to Be in High Demand in 2014

“Computerworld cited analytics expertise as the second-hardest IT skill to find, hinting that the six-figure salaries these professionals command may be worth every penny. Eighteen percent of survey respondents reported that they intend to hire for this critical need in the next year.” Original Source: http://midsizeinsider.com/en-us/article/business-analytics-among-it-skills-expec

 

Analytics Driven Business Decisions

“Many of the organizations engaged in big data analytics programs report that their programs are increasingly adding advanced capabilities to find patterns in the inherent complexity of multiple data sets and structures. In order to accomplish this, respondents are applying optimization models and advanced analytics towards business process improvement”

Original Source: http://eyeonibm.com/2012/11/05/analytics-driven-business-decisions-skills-competencies-and-methods-used-by-survey-respondents-to-transform-their-business-decisions-so-that-they-are-analytics-driven/

 

In Big Data Endeavors, Don’t Neglect Softer Business Skills

“But the ability to communicate, relate and navigate throughout an organization—so called “softer skills”—are especially needed to propagate analysis and communicate the impact of data-driven decision-making.”

Original Source:http://www.customerthink.com/blog/in_big_data_endeavors_don_t_neglect_softer_business_skills

 

Conclusion

Supply Chain Analytics practitioners and supply chain consultants need to have the ability to see the big picture, they must have the technical expertise as well as the operational knowledge and communications skills.

3 Ways to Use Supply Chain Analytics to Drive Profitability

Supply Chain Analytics are not only used for realizing cost savings opportunities. Supply Chain Analytics also offer great untapped potential for increasing operational performance. Three important applications that will drive profitability and growth include: 1. Building supply chain models that provide actionable insight, 2. Connect demand and supply in real-time and 3. Analyze supplier risk.

 

Build Supply Chain Models that Provide Actionable Insight

 

According to Edith Simchi-Levi, Supply Chain Analytics requires a deep understanding of supply chain management and operations—as well as the modeling and mathematical techniques that will provide true, actionable insight into how to improve operations. “This involves first building a model of the current system, what’s called a baseline, and then validating by comparing the model with results, the details of the business. This is actually a pretty complicated process.”

“…sometimes the models are just something new and surprising that you probably wouldn’t have been able to come up with without the model, but sometimes the surprise indicates some sort of a problem with the data or the assumptions, and it would require reviewing any discrepancies to see, to really understand them and make sure that the model is reflecting reality correctly.” Original Source

Check out this video on The Role of Analytics in Supply Chain and Operations Strategy:

Connect Demand and Supply in Real Time

“One of the most important attributes of next-generation supply chain analytics is that they will address issues beyond the supply chain. To optimize operations, companies need to link their supply chains with metrics and analytics on the demand side. For example, at the simplest level, price changes or promotions for products will change demand and hence the required supply of those products. Similarly, changes in the availability of products and components should be reflected in marketing and sales processes.” Original Source

 

Analyze Supplier Risk

“Many companies recognize that the success of their operations is highly dependent upon their suppliers. Yet supplier risk analytics have hardly moved beyond simple metrics and reports in most organizations. The most sophisticated approaches to supplier risk monitoring and management—used by companies that heavily depend on external suppliers and contract manufacturers, such as Cisco Systems—are only somewhat more analytical.” Original Source

 

Conclusion

There are many opportunities for applying supply chain analytics to your business. Facts matter when they are collected from the source and handled close to the reality with the right expertise and tools. Facts can improve efficiency, drive profitability and growth.

The Biggest Obstacle to Successful Supply Chain Analytics

Supply Chain Analytics tools and methods open up the opportunity to drill deeper into supply chain data for finding more ways to save money. However, the biggest obstacle to success are organizational silos and the silo mentality. This is because coordination across departments is where the greatest opportunities lie to create efficiency. Data democratization is the solution to this problem of silos in the organization.

Most large companies still work with siloed departments. Each department has little to no idea what another is doing. They usually each drive their own programs without communicating with each other, and they are rarely aligned.

Hadoop success requires avoidance of past data mistakes

“An organizational silo, like a data silo, has lots of inputs but few outputs: it’s a people bottleneck. Too often if a business analyst wanted data they had to go to a central analytics team, wait in line, get the analytics team to understand their need, wait a few days for the results, realize that the results weren’t what they thought they’d asked for, and repeat the process until one side gave up. Then when business analysts complain and ask why on earth it could take so long, analytics just says, “There’s a lot of math involved. You wouldn’t understand.””

Original Source: http://www.techrepublic.com/blog/big-data-analytics/hadoop-success-requires-avoidance-of-past-data-mistakes/

 

Why CIOs Should Care About Supply Chains, Procurement

 

“To achieve real-time analytics, companies will need to change that by opening the black box silo and integrating the data with other enterprise systems. Of course, this is the sweet spot for middleware companies like Software AG, whose solutions can open up that data.

This is something enterprise technology journalists typically have not covered because B2B systems have operated in a silo, separated both by technology and by responsibility from other enterprise systems.”

http://www.itbusinessedge.com/blogs/integration/why-cios-should-care-about-supply-chains-procurement.html

 

Silos in the Supply Chain

 

“The silo problem that Nagaraja observes in the technical architecture of companies can normally be found across the spectrum of activities in which companies engage. Catherine Bolgar advises that companies must avoid “the gaps in corporate performance” created by silos [“Silos,” Zurich Financial Supply Chain Risk Insights, 24 May 2010]. She writes: “It takes a lot more for a company to succeed than for each employee to do his part. A company is composed of many opposing interests. Product designers want the best materials, but purchasing managers want the cheapest. The finance department wants the leanest possible inventories, but the sales department wants large stocks in order to sell big orders with a promise of quick delivery. The competing departments are like the proverbial blind men exploring an elephant, each perceiving the animal from a narrow perspective. These management silos can undermine the best business resiliency plans and pose problems for supply-chain and risk management.” “

http://enterpriseresilienceblog.typepad.com/enterprise_resilience_man/2010/06/silos-in-the-supply-chain.html

Good companies break down silos by implementing cross-functional teams. They get the teams working together on supply chain analytics projects. They share data and make it easy to send and receive information. Successful supply chain analytics requires analytic tools and the systems mentality to apply them across silos.

3 Reasons Why You Should Do Supply Chain Analytics

Supply Chain Analytics is used to help companies gain a competitive advantage. We look at the information collected from a host of supply chain measures and then draw conclusions. We can do “what-if” analysis as well as assess where profitability will be impacted.

The 3 reasons why we should do supply chain analytics:

1. Make better supply chain decisions while reducing waste

2. Model profitability impacts

3. Gain competitive advantage

Supply Chain Analytics: What is it and Why is it so Important?

Supply chain analytics is an art and science to looking at raw data with the aim of drawing conclusions about information. The goal is to help a company make better supply chain decisions while reducing waste and increasing supply chain performance.

Rising fuel costs, off-shoring, and increased competition from low-cost outsources are some of the driving forces for doing supply chain analytics.

Original Source: http://www.industryweek.com/blog/supply-chain-analytics-what-it-and-why-it-so-important

 

The Role of Analytics in the Race for the Supply Chain of the Future

We need to both understand the supply chain as a complex system and have the ability to perform effective use of data. According to Lora Cecere, “only 11% of companies have the capabilities that they need to evaluate a “what-if analysis” and only 24% of companies are able to model profitability impacts of changing conditions in their complex systems.”

Original Source: http://data-informed.com/role-analytics-race-supply-chain-future/#sthash.pwYV2cwR.dpuf

The What, Why & How of Supply Chain Analytics

We need to match not only knowledge of mathematical techniques but also knowledge of the supply chain. Supply chain analytics is an area of investment and competitive advantage for many companies. Supply chain analytics helps companies understand what their business is doing as well as come up with new solutions and ideas for where they are going.

Original Source: http://www.opsrules.com/supply-chain-optimization-blog/bid/297730/The-What-Why-How-of-Supply-Chain-Analytics

Establish Davis Database Presentation at CSCMP

Establish’s consultants Conrad Ross and Piotr Pregner will be presenting the 2013 Establish Davis Logistics Cost and Service Database at the CSCMP annual global conference in Denver 22 October.

Establish Davis Logistics Cost and Service Database is an ongoing annual survey that manufacturers, distributors and retailers participate in to receive a customized logistics benchmarking report of logistics cost and service. The benchmarking database is the longest running, since 1976, and with most entries in the logistics industry. The findings are presented annually at the Council of Supply Chain Management Professionals (cscmp.org) Annual Global Conference. Participation in the Database is free and confidential. It’s easy to participate on-line and our logistics consultants are ready to help you, should you have any questions.

Internal Business Partnering in Procurement

Dustin Mattison interviewed Bill Young. Bill discussed Internal Business Partnering in Procurement.

Internal Business Partnering

Bill believes Internal Business Partnering is important because category management has been mainly about cost reduction and a lot of companies have been through at least one, two, sometimes three phases of category management. The result is that they have plowed the fields and saved a lot of cash. Now purchasing is starting to look at how it can create value, as well as just reducing costs. In order to do that, they need to be much, much closer to their internal clients, but some of those internal clients are suspicious of purchasing because they have some experiences of having their budgets raided. Bill says that purchasing has perhaps a little bit of ground to catch up on before it’s fully trusted as a business partner.

Internal Business Partnering is really a form of consultancy. It’s being the expert on how supply markets work; what you can get out of supply markets; how you can manage them better; how you can improve their efficiency and effectiveness; how you can extend the resources of the organization beyond its direct employees and into the companies that provide it with important services; extending the scope of the resources of a company.

According to Bill what we’re seeing is that IT departments in many companies have already taken purchasing back into their function. You can see companies where they have IT strategic sourcing managers in effect doing exactly what purchasing wanted to do and used to do, and they’ve hollowed out that bit of procurement. The same could be happening in HR, where, if you look at the average HR department, approximately fifty percent of everything they provide to the business is actually coming from external suppliers. They need to have some sort of core competence within the HR function and managing those suppliers, and they’re asking, “Why would we get procurement to do this if it’s so important?” The future of procurement depends on stepping up to the plate and learning how to do this business partnering; otherwise, some of these departments are gonna take it in-house, as IT already has done.

His recommendations are that companies should obviously think hard about Internal Business Partnering in Procurement. It tends to be the service companies that are pioneering this area, and they include the advertising companies, the media companies, a lot of the Internet companies. In fact, Bill saw recently a job description for what looked to any other company like a category procurement manager at Amazon. The words procurement, purchasing, and buying didn’t appear in the job description. He thinks the next stage is going be the high-service companies but still with manufacturing elements, especially pharmaceuticals. They should be looking hard at this area and looking at the transition. The interesting thing will be for a lot of companies who never really fully embraced category management, can they go straight from classical procurement to value procurement? Some have but it’s a big step. So, looking at this area, looking at the skill levels and facing the challenge, that’s the next phase.

About Bill Young

Development of Sales and Procurement Capability

LinkedIn Profile

Questions To Ask When Collaborating With Suppliers

Dustin Mattison interviewed Sara Husk. Sara discussed collaboration with suppliers and customers.

Sara works for a company called Imaginatik. Imaginatik specializes in providing innovation infrastructure both from a technical and services perspective, primarily to Fortune500 companies. Sara works with a lot of companies on their innovation program on a day to day basis.

One of the things Sara and her team is noticing is that companies increasingly want to go outside of their four walls to collaborate, innovate and develop new things. This can be with customers, suppliers or vendors. They really want to get the most that they can out of the entire group they are working with. It can be partners, universities, community groups, state regulatory groups, etc. These things can all help bring value back to the company.

The first things Sara usually asks are “why do you want to get into this?”, “what is it you are hoping to gain?”, “what does success look like?”, “what are those intangible outcomes?”.

The tangible outcomes might be to get some type of new way of manufacturing a part. Intangible might be to build a strong relationship with suppliers so that they bring some of their best and creative ideas.

You are also looking at things like why you want to be the brand of choice in the marketplace to be the group to collaborate with. You also need to think about who owns the outcome and how to handle these types of pieces as well. There is a lot that goes into it in terms of the thought process up front.

There are a lot of things that are involved with thinking this whole thing through. You need to ask questions such as: How do you get people aligned with you? How do you get people participating with you? What is in it for the other parties?