Big Data – Is Your Supply Chain Ready?

You receive a notification on your phone that a critical shipment from your China factory has missed its filing deadline with the customs broker.

Your logistics manager is alerted that there is an 80% chance that the components he’s waiting for are likely to be delayed another 48 hours by excessive port traffic and your GTM software advises diverting the shipment to an alternate port facility.

Your compliance officer is informed that there is a 95% chance that a shipment of parts from Malaysia is likely to be held for up to three days to be subjected to a detailed customs inspection.

If you think this type of information would be of great assistance to your supply chain business planning and operations, you are not alone. It is this type of integrated data and communications that are becoming the backbone of the Big Data led revolution underway in the supply chain.

The human brain can only process and make use of a limited amount of information before it becomes overwhelmed and unable to effectively recognise patterns and trends. But powerful algorithms and the software platforms they drive can take in almost unlimited numbers of data points and process them to generate insights impossible for an individual or even an entire organisation of individuals to identify. And powering this technology-driven transformation of the supply chain is Big Data.

Big Data vs Small Data

To really understand how technology is transforming supply chain, it is important to understand how Big Data differs from any other form of information gathering. Data has always been crucial to efficient supply chain operations so what has actually changed in recent years? How is “Big Data” different from the analysis of “small data” that has always occurred in the industry?

Big Data refers to sets of both structured and unstructured data with so much volume that traditional data processing systems are inadequate to cope with it all. It can be further defined by some of the basic properties that apply to it:

Variety – data being generated from a wide number of varied sources

Volume – while there is no set distinction between where small data stops and Big Data starts, Big Data requires large storage requirements for the data, often measured in many multiples of terabytes

Velocity – the speed at which the data can be acquired, transferred and stored

Complexity – difficulties encountered in forming relevant relationships in data, especially when it is taken from multiple sources

Value – the degree to which querying the data will result in generating beneficial outcomes

The most important property related to Big Data is as the name implies, volume. We normally think of data purely in terms of text or numbers but it can include everything from the billions of emails, images, and tweets generated every day.

In fact, data generation is expanding at a rate that doubles every two years. And human and machine-generated data is growing at 10 times the rate of traditional business data.

IT World Canada projects that by 2020, you would need a stack of iPad Air tablets extending from the earth to the moon to store the world’s digital data.

But the real focus behind a preference for Big Data analysis over small data systems is the ability to uncover hidden trends and relationships in both structured and unstructured data. In most cases, using small data collection and analytics processes simply cannot identify crucial information in a timely manner to allow key decisions to be made or opportunities to be taken advantage of. In other cases, using small data systems is simply a waste of resources and leads to disruptions to supply chain operations.

By contrast, if used correctly Big Data is the key to enhancing supply chain performance by increasing visibility, control, agility, and responsiveness. Making decisions based on high-quality information in context can benefit the full range of supply chain operations – from demand forecasting, inventory and logistics planning, execution, shipping, and warehouse management.

Big Data possibilities

Big Data analytics becomes a vital tool for making sense of the huge volumes of data that are produced every day. This data comes from a whole range of activities undertaken by people associated with supply chain, whether they be customers, suppliers, or your own staff. The range and volume of this data are continuously increasing, with billions of data points generated by sources we see as directly linked to supply chain such as network nodes and transaction and shipping records as well as other areas that more indirectly impact supply chains such as retail channels and social media content.

But it is increasingly becoming necessary to harness this data in order to remain competitive. This is evident from statements such as the below:

“Big Data is certainly enabling better decisions and actions, and facilitating a move away from gut feel decision making.” -Anthony Coops, Asia Pacific Data & Analytics Leader, KPMG Australia

At the same time, he recognises that solutions need to be put in place that allows for people and organisations to have complete faith in the data so that managers can really trust in the analytics and be confident in their decision making.

The need for confidence in the analytics is evident when considering the examples such as where GTM software has the information and capabilities to advise ahead of time to divert shipping stock to an alternate port or that a product is likely to be held up in customs. These types of decisions have potentially large financial consequences but when implemented correctly, it is easy to see how supply chain operational efficiency can be significantly boosted by effective use of Big Data analytics.

Many organisations are also using Big Data solutions to support integrated business planning and to better understand market trends and consumer behaviours. The integration of a range of market, product sales, social media trends, and demographic data from multiple data sources provides the capability to accurately predict and plan numerous supply chain actions.

IoT and AI-based analytics are used to predict asset maintenance requirements and avoid unscheduled downtime. IoT can also provide real-time production and shipping data while GPS driven data combined with traffic and weather information allows for dynamically planned and optimised shipping and delivery routes. These types of examples provide a glimpse into the possibilities and advantages that Big Data can offer in increasing the agility and efficiency of supply chain operations.

Disruptive technologies

What is driving these possibilities is the development of numerous disruptive technologies as well as the integration of both new and existing technologies to create high-quality networks of information. Disruptive technologies impact the way organisations operate by forcing them to deal with new competitive platforms. They also provide them with opportunities to enter new markets or to change the company’s competitive status.

By identifying key disruptive technologies early, supply chain organisations can not only be better placed to adapt to changing market conditions, they can also gain a distinct advantage over others in the industry that are reluctant to embrace change.

In terms of Big Data based disruptive technologies, these are largely driven by the effects of constantly evolving and emergent internet technologies such as the Internet of Things combined with increased computing power, AI and machine learning based analytics platforms, and fast, pervasive digital communications. These technologies then act as drivers that spawn new ways of managing products, assets, and staff as well as generating new ways of thinking about organisational structures and workflows.

IoT

After being talked about for many years, we are now starting to see the Internet of Things really taking shape. There will be a thirty-fold increase in the number of Internet-connected physical devices by 2020 and this will significantly impact the ways that supply chains operate.

IoT allows for numerous solutions to intelligently connect systems, people, processes, data, and devices via a network of connected sensors. Through improved data collection and intelligence, the supply chain will benefit from greater automation of the manufacturing and shipping process becomes possible through enhanced visibility of activities from the warehouse to the customer.

Cloud-based GPS and Radio Frequency Identification (RFID) technologies, which provide location, product identification and other tracking information play a key role in the IoT landscape. Sensors can be used to provide a wealth of information targeted to specific niches within supply chain such as fresh produce distribution where temperature or humidity levels can be precisely tracked along the entire journey of a product. Data gathered from GPS and RFID technologies also facilitates automated shipping and delivery processes by precisely predicting the time of arrival.

Big Data analytics

Big Data analytics encompasses the qualitative and quantitative techniques that are used to generate insights to enhance productivity. The more supply chain technologies are reliant on Big Data, either in their business model or as a result of their impact on an organisation, the more organisations have to rely on the effective use of Big Data analytics to help them make sense of the volumes of data being generated. Analytics also helps to make it possible to understand the processes and strategies used by competitors across the industry. Using analytics effectively allows an organisation to make the best decisions to ensure they stay at the forefront of their particular market sector.

As corporations face financial pressures to increase profit margins and customer expectation pressures to shorten delivery times. the importance of Big Data analytics continues to grow. A Gartner, Inc. study put the 2017 business intelligence and analytics market at a value over USD$18 billion, while the sales of prescriptive analytics software is estimated to grow from approximately USD$415 million in 2014 to USD$1.1 billion in 2019.

Over time, the effectiveness and capabilities of analytics software also continue to improve as machine learning-based technologies take forecast data and continually compare it back to real operational and production data. This means that the longer an organisation operates its analytics software, the iterative nature of artificial intelligence powered algorithms means that the performance and value of the software improve over time. This leads to benefits such as more accurate forecasts of shipping times or supplier obstacles and bottlenecks.

Consumer Behaviour Analysis

Although it may not initially seem as vital to supply chain as other disruptive technologies, consumer behaviour analysis can have a huge impact on businesses working in supply chain, especially e-commerce businesses. Known as clickstream analysis, large amounts of company, industry, product, and customer information can be gathered from the web. Various text and web mining tools and techniques are then used to both organise and visualise this information.

By analysing customer clickstream data logs, web analytics tools such as Google Analytics can provide a trail of online customer activities and provide insights on their purchasing patterns. This allows more accurate seasonal forecasts to be generated that can then drive inventory and resourcing plans. This type of data is extremely valuable and is crucial for any organisations operating in the e-commerce space. While retailers and consumer companies have always collected data on buying patterns, the ability to pull together information from potentially thousands of different variables that have traditionally been collected in silos provides enormous economic opportunities.

Potential drawbacks and challenges

Despite the huge opportunities presented by implementing Big Data powered solutions, there can be intimidating barriers to entry when it comes to putting in place Big Data collection and analytics solutions. This can emerge across a range of areas including the complexities around data collection and the difficulties of putting in place the technologies and infrastructure needed to turn that data into useful insights.

Getting complete buy-in

One impediment to adopting a holistic Big Data approach centres around having unified support at all levels of your company to adopt comprehensive Big Data systems. Management commitment and support is crucial and large-scale initiatives of this type usually occur from the top down. However, Big Data analytics type initiatives usually originate at mid-level, from people who actually collect and use data day to day. This means that for this issue, the need for implementation must often be sold upwards. In some cases, upselling the importance of Big Data to management that doesn’t understand why that type of expense is necessary is extremely challenging.

Sourcing clean data

One of the other main challenges is undoubtedly sourcing appropriate and consistent data. There’s no use getting high-quality data if it doesn’t directly apply to your particular market sector. Nor is there much benefit to be gained from obtaining high-quality data but being unable to consistently source it at the same regularity to enable it to build a long-term profile of the company’s operations and market forces. These challenges are often related to technical issues such as integration with previously siloed data or data security concerns.

Richard Sharpe, CEO of Competitive Insights, a supply chain analytics company, believes that the data quality problem is a complex issue that can have many different causes. However, he believes that these challenges can be overcome by management having a clear understanding of what they’re trying to achieve. “You have to show that what you’re ultimately trying to do with supply chain data analytics is to make the enterprise more successful and profitable.” This then leads to support being provided by company leadership who, in tandem with operations managers, can develop the processes required to govern quality data collection. This includes proper consultation with subject matter experts who can help ensure that all data is properly validated.

Managing data volumes

New technologies make it possible for supply chain organisations to collect huge volumes of information from an ever-expanding number of sources. These data points can quickly run into the billions, making it challenging to analyse with any level of accuracy or lead directly to innovation and improvement.

This means that despite many organisations embracing Big Data strategies, many do not actually derive sustainable value from the data they’re accumulating because they begin to drown in the sheer volume of data or don’t have the appropriate software and management tools to make use of it. A common phrase used to summarise this effect is “paralysis by analysis”. Without a thorough understanding of the technologies and systems needed to process and store the data collected, this can be an easy condition for an organisation to become afflicted by.

Building the infrastructure

Companies need to invest in the right technologies to have a true 360-degree view of their business. And in many cases, these technologies can involve large initial capital outlays. Getting the infrastructure in place is key to being able to collect, process, and analyse data that enables you to track inventory, assets and materials in your supply chain.

Putting in place the infrastructure may also require additional training expenses, so that staff are properly trained in how to use new software platforms or to maintain sensors and other new IoT devices. In some cases, this will extend to requiring hiring new talent capable of using and interpreting new analytical tools.

Conclusion

Big Data offers huge opportunities to supply chain organisations, as vital information contained within multiple data sources can now be consolidated and analysed. These new perspectives can reveal the insights necessary to understand and solve problems that were previously considered too complex. New insights can also encourage organisations to scale intelligent systems across all activities in the supply chain, embedding intelligence in every part of the business.

There is also no doubt that implementing comprehensive Big Data solutions can involve new and significant challenges. However, once the new infrastructure and processes are in place, the nature of modern Cloud-based networks allows for data to be accessed easily from anywhere at any time. It also allows for other benefits beyond cost reduction and production gains to be realised over time, such as ongoing rather than just one-off efficiency gains and improved transparency and compliance tracking across the entire organisation.

See original blog here

 

About the Author

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Bastian Managing Director, Tony Richter, is a supply chain industry expert with 7+ years executing senior supply chain search across APAC. He works exclusively with a small portfolio of clients and prides himself on the creation of a transparent, credible, and focused approach. This ensures long-term trust can be established with all clients and candidates.

To find out more about the challenges and opportunities offered by Big Data to supply chain, or to gain a deeper understanding of the technology and Big Data trends currently underway in the industry, talk to an industry expert at http://bconsult.io/

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Supply Chain Planning & Optimisation Projections for 2018 – Back to the Future

By Henry Canitz, Director of Product Marketing and Business DevelopmentPicture1

I get a kick reading “prediction” articles both prior to the year start and then again after the year is complete. When it comes to predicting the very dynamic supply chain management industry, those after year reviews can be quite amusing. For even more fun look back 10 or more years to see where we all thought the industry would be. Therefore, it is with a bit of trepidation that I toss my hat in the arena and make my 2018 supply chain planning and optimization predictions.

From all indications, 2018 should be a very interesting year for supply chains and supply chain practitioners. I think there are a few advanced capabilities that will grow in importance but I also believe there is a growing awareness that to benefit from advanced planning and optimization capabilities a company needs to build a firm foundation. Companies need a robust integrated and highly functional supply chain platform that is operated by highly trained supply chain professionals. In a way, we need to go back to fundamentals to move forward to the future.

The Rise of Cloud Deployment and Heightened Security

The large number of major data breaches in 2017 has been the focus of many C-level meetings. In an interesting reversal, SaaS (software-as-a-service) solutions are now viewed by most as the least risky deployment option and this will increase in the year ahead. 2018 will bring a renewed emphasis on security for supply chain facilities due to the growing awareness that data breaches can originate through almost any type of connected system and the fact that more facilities are being opened in unstable geographies.

The Shift to Continuous Planning

The pace of the supply chain is increasingly driven by ever-growing customer expectations (Amazon Effect) making end of the day, week, or month periodic planning processes, while still important, no longer sufficient for today’s operations. The concept of continuous planning where planners address opportunities and disruptions as they happen will continue to gain ground in 2018. These efforts could be part of a Sales and Operations Execution (S&OE) process or tightly tied to building more robust digital planning and optimization capabilities. To facilitate continuous planning process companies will start to move towards cross-functional teams working in a control-room type environment to address global disruptions and opportunities using advanced planning and optimization capabilities.

Digitisation

You can’t open a recent supply chain periodical today without seeing something about artificial intelligence (AI). Advanced analytics, machine learning, algorithmic planning, and AI will all continue to capture a significant slice of attention in 2018. In the year ahead, this will require supply chains to shift how they operate. With digitization of the supply chain, the role of the planner will become one of solving problems using advanced analytics to make business decisions not just supply chain decisions.

The Internet of Things (IoT) will continue to drive supply chain execution innovation as companies find new opportunities in the wealth of data available. For many, the current state includes difficulties interfacing IoT data in a high quality, repeatable fashion. Most companies just aren’t at the point where consuming this firehose of data is feasible.

Supply Chain Data Quality and Ownership

Supply Chain Master Data Management (MDM) is quickly becoming a critical foundational requirement and I expect to see more interest in this area in 2018. Much of the data used for supply chain planning and execution comes from outside of a company’s ERP systems. Ask yourself, where is supply chain data maintained at your company today? The answer might surprise you. Effective supply chain planning and optimization requires high quality and consistent data and the ability to easily and quickly maintain and update that data. Inconsistent and poor quality data will degrade confidence in recommendations. One of my mentors once told me that, “One awe S#?* wipes out 1000 Attaboys (or Girls)”. One piece of bad data that tarnishes a recommendation will be difficult to overcome. To take full advantage of IoT data, supply chain organizations will need to invest in their Supply Chain Master Data Management capabilities and platforms.

Talent GapPicture12

You continually hear from hiring managers that there is a “War for Talent” driving increased salaries, benefits, and turnover rates for supply chain professionals. This will not change anytime soon. Actually, with a shrinking baby-boomer workforce the war for talent is only going to heat up in 2018 (read more here: The Talent Gap and here: Imagine 2030: Supply Chain Talent). Companies will need to find additional ways to attract and retain talent like rotational programs, clear-cut career paths, advanced degree support, and support for professional training. Another way is to provide advanced supply chain platforms that allow team members to work on more value-added activities. Yes, the ability to hire and retain talent could be another way to justify an investment in new supply chain planning and optimization capabilities.

Taking S&OP to the Next Level

I have personally seen the significant benefits of a well-run S&OP process and I know other practitioners have as well. I may be going out on a limb here but I think 2018 will be the year of renewed efforts around putting advanced S&OP capabilities in place including the ability to;

  • Optimize the end-to-end supply chain based on constraints and business objectives (minimize cost, maximize profits, meet customer service levels, etc.)
  • Analyze the impacts of product-lifecycle decisions, especially new product introductions
  • Align and synchronise strategic, tactical and operational planning
  • Collaboratively plan with partners and customers

A year from now I am sure we will all get a good laugh by revisiting this piece, but I am hopeful that a least of few of my predictions will hold true. Here’s to a happy and successful 2018.

About the author 

Hank Canitz PictureHenry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.

Is Your Supply Chain Planning System in the Cloud?

Supply Chain in the Cloud - 310 x 175My job requires a fair bit of air travel so I literally spend a good deal of my time with my head in the clouds. At 6’5” most airline seats are less than comfortable and provide very little leg, arm and shoulder room, so I often find the most practical activity during a flight is critical thinking. Yes, I might look like I am taking a nap but really I am deeply contemplating things like the current state of deploying Supply Chain Planning Technology in the cloud.

With the explosive growth in supply chain complexity and data volumes, a growing number of manufacturers, retailers and distributors of all sizes are all looking for more agile, easily implemented paths to better supply chain performance. Some have found it possible to enact powerful supply chain optimisations almost immediately, while saving substantial amounts of working capital and ensuring timely support for growth and collaboration over the long term.

They have chosen to deploy supply chain planning solutions in the Cloud.

Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort.

Today, the range of implementation options for supply chain planning solutions stretches far beyond traditional on-premises hardware and software. Some competitive-minded organizations question the advisability of lengthy and complex infrastructure projects. These supply chain teams harness the full potential of the internet by taking advantage of deployment models with names like Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and managed services.

Cloud-based deployment alternatives remove IT obstacles and accelerate the launching of supply chain initiatives. However, are the advantages of cloud deployments for supply chain solutions real and worthwhile? I think so, and I have provided a few of the biggest benefit areas for having your supply chain planning software in the cloud.

Benefit #1: Affordability and Savings

  • Lower upfront costs – Initial capital equipment expenses are reduced and total cost of ownership shifts to a highly predictable annual expense line item.
  • Optimal licensing, hosting and services options – The wide variety of options provide a solution delivery profile that fits just about any organisation’s software procurement model and budget process.
  • Ability to reallocate valuable IT resources – Cloud-based deployments free up enterprise IT resources to focus on strategic initiatives and meet mission-critical demands rather than installing software updates and performing system administration.
  • Scalability to handle supply chain growth – It’s a significant competitive advantage to be able to activate capabilities as requirements grow and flex over time.

Benefit #2: Tangible Business Benefits

  • Accelerated ROI – Cloud deployments often deliver better cash flow and create a positive bottom-line impact much quicker than traditional models.
  • Greater agility to react to change – Because “the infrastructure is on the internet,” there is no hardware to implement and no software to install. Users can access the system from any location through web-connected laptops, tablets and smart phones.

Benefit #3: Reliability and Security

  • Less risk of unscheduled downtime – Resiliency and high availability are characteristics of a well-designed cloud-based deployment.
  • Robust security – The fear that storing business data on a cloud server could make it vulnerable to unauthorised access has been assuaged by the great security track record of hosting providers in securing and ensuring data privacy.
  • Expert administrative services – No one knows the ins and outs of system administration better than the solution provider organisation itself. The provider’s technical personnel are an essential resource for installing software updates, hot fixes, service packs and version updates in an optimum computer environment.

According to Gartner, cloud computing has reached a sufficient level of maturity to be in its “productive phase.” In fact, cloud-based solutions have proven enormously successful in a broad range of commercial applications, revolutionising the affordability and “adoptability” of solutions for a much wider range of companies. It is time for Supply Chain Planning solutions to join in this success?

As you consider the benefits of a cloud-based supply chain planning solution, conduct a self-evaluation by asking these questions:

  1. Does your current supply chain planning technology infrastructure fall short of the task of providing the supply chain planning capabilities you need?
  2. Is it difficult in your organisation to drive new capital investments for updated equipment and systems?
  3. Is your IT staff overwhelmed with user support issues and other system administration tasks?

If the answer to any of these questions is “yes,” then it’s time to find out how a cloud-based solution can accelerate one of the most rewarding business improvement initiatives your organisation can undertake: Optimising your Supply Chain.

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About the author

Hank Canitz PictureHenry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.