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Supply Chain Management in QlikView / Qlik Sense

With complicated structure in a supply chain, it has been a challenge for executives to see and understand the associated changes and movements in a supply chain. Examples are raw materials, inventory, products, marketing campaigns, promotions, and other supply chain activities.

As brands and products proliferate, are spun off, and re-consolidated, supply chain companies find themselves struggling to understand what they have, what they need, and where they’re going. Doing so requires a tremendous amount of data, drawn from both external sources (suppliers, partners, customers) and internal ones (marketers, production managers, supply chain groups). The ability to see all of the data surrounding a brand at a glance is a tall order, one only made harder by the proliferation of systems and processes designed to support it. Before companies can profit from efficiencies of scale, they need to consolidate these systems. This is an area where business intelligence (BI) can help them.

However, melding disparate data sources through business intelligence turns out to be a disaster, when companies are using multiple technologies under one roof. These technologies could be from Microsoft, Oracle, SAP, IBM, Teradata, and others. People are struggling before BI implementation, and people are struggling even more after it. As a result, instead of placing information in the hands of the managers who needed it, they are now locked inside those data and technologies, where they could barely get to the real BI they desperately need. On the other hand, IT departments are struggling with questions like: “how many people I needed to build reports”, “how long it is going to build reports”, and “what those reports should look like”.

To meet the challenges of data and technologies, a possible solution is QlikView or Qlik Sense from Qlik. Compared to other BI vendors, the most unique feature of QlikView / Qlik Sense is that people don’t have to think about the joins of tables; people don’t even have to think about which tables to pull out of their ERP. The appliance just bolts onto the side and sucks the whole thing out. People, or even non-IT people, can spent a week extracting the relevant data tables from the central data warehouse, then loading them into QlikView / Qlik Sense as individual data sets — one for sales, one for materials management, and so forth. And, suddenly, they can gaze across a total landscape of its supply chain before drilling down by product or brand or segment or market — or any combination it liked.

With QlikView / Qlik Sense, companies can train or hire a handful of savvy managers who in time became the trainers for their respective divisions. When the need arises for a report, they’ll point you to an existing report or enhance it or build a new one if need be, if everyone agrees it’s the right thing to do. People are taking reports into their own hands and customizing them to suit their needs.

In addition to this special feature, people can also implement their supply chain management BI by using one of the following templates in Qlik Demo site:

  • Executive Insights
  • Production Insights
  • Forecasting and Planning
  • Sourcing and Supplier
  • Regulatory Compliance
  • IT Management
  • Warehousing and Distribution
  • Transportation and Logistics
  • Merchandise Management

In addition, people can find other supply chain solutions provided by Qlik vendors at the Qlik Market. A screenshot of the Order and Inventory Management Dashboard is enclosed below. You can go to its interactive demo site here.

Order and Inventory Management.qvw

In summary, supply chain management is implemented in QlikView / Qlik Sense as applications or reports in all areas of the supply chain management, which can come from one of a reports template Qlik provides, custom made to match what you have today, or created by one of its vendors. The applications and reports do not need specialized IT departments to create and can be created by your very own people in the field.

References:

 

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Data Science Is Dead

This article gives a very good criticism about the popular Data Science / Data Scientist these days. Data Science is something business people invented as a creative way for a new profession as a result of Big Data. “Science” is about creating knowledge as a result of study / research. Consequently, “Data Science” should be about creating knowledge through the study of data, not just data analysis, a/b testing, or troubleshooting which almost the majority of business people are doing. Essentially, the article claims data analysis / data troubleshoot is NOT Data Science.

Today it is a big hype for companies to look for Data Scientists with unrealistic expectation in those job ads. They are looking for a miracle medicine but a quick fix to data which they are unable to handle today. As a result, a short cut is taken and a new profession is created. Major software companies even invent new products to automate the jobs of Data Scientists! It is just like the story of the King’s New Robe. When a king was naked with an imaginary rob and walking down the street, everyone was so ashamed to be called stupid that they never called out the imaginary robe as a lie, not until kids, with their pure and untainted mind, laughing at the king’s stupid belief. The story was repeated to supply chain management (SCM) and is repeated to Big Data and Data Science today. People are so ashamed to be called stupid so they just follow the trend and try to build empires out of the trend. Companies are spending billions of dollars to just make reports as eye candy but do not really know how to use them to improve their bottom lines.

… you’ll realize that the “Big Data” vendors have filled your executives’ heads with sky-high expectations (and filled their inboxes with invoices worth significant amounts of money) …

The author claims there is no data science until you are working on “structured” data, where is most statistics draws its inference for prediction and control. The author emphasis the importance of “cleaning off the rotten banana peels” before you look at data so you won’t draw biased conclusion, which is totally against the idea of Big Data today.

I understand the importance of having fresh idea to keep people engaged in our advancement. Putting emotion aside, if possible, this article does provide a very bitter but true advice to Data Scientists.

Don’t be the data scientist tasked with the crime-scene cleanup of most companies’ “Big Data”—be the developer, programmer, or entrepreneur who can think, code, and create the future.

Reference: Data Science Is Dead

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2013 in review: Big data, bigger expectations?

In the parlance of the industry, big data’s feat was a result of the successful convergence of the “three Vs”:

Volume: A large amount of data

Variety: A wide range of data types and sources

Velocity: The speed of data moving from its sources, into the hands of those who need it

Although other Vs have since been contemplated, such as Veracity and Value, the original three attributes promised big data could go far beyond the boundaries of traditional databases, which require data to be stored in rigid rows and columns.

However, over the past year, reality began to sink in: People came to realize what big data could and could not do. Unfortunately, performing large-scale analytics in real time proved to be more daunting than originally thought. Although Hadoop continues to be the world’s most popular big data processing platform, it was designed for batch processing and is far too slow for real-time use.

Reference: 2013 in review: Big data, bigger expectations?

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Apple’s challenges in ensuring fair treatment of workers in complex supply chains

Bloomberg has a lengthy piece illustrating just how great a challenge it is for Apple and other multinational companies to ensure the fair treatment of workers in complex supply chains.

When one of Apple’s suppliers like Flextronics wins a new contract, it needs to take on additional workers – lots of them, and fast. Those workers are recruited through employment brokers, which are required to adhere to Apple’s rules. But many of them are brought in from other countries, like Malaysia and Nepal.

Alok Taparia, the managing director of Transworld Manpower, another of the four Nepalese brokers retained for that drive, says he was given clear instructions: Workers shouldn’t be charged; Flextronics would pay the brokers. But Taparia and the other Nepalese brokers say Flextronics demanded so many men so quickly that there was no way to do it without tapping the country’s network of subagents, stretching into Himalayan villages reachable only by foot. As Apple itself has described in reports on its supply chain, the subagents always charge…

Workers recruited from neighbouring countries can end up needing to pay several layers of agents and sub-agents for their jobs. Without the cash to do so, they take on loans – and are required to surrender their passports as security. The piece says that Apple’s attempts to deal with this are proving less successful over time.

Labor demand surge remains a challenge to our supply chain today. Feel free to contact us, if you need help with your supply chain.

Reference: Apple’s challenges in ensuring fair treatment of workers in complex supply chains

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New Supply Chain Trend: Amazon Moving In With Manufacturers

Moving In With Manufacturers, Amazon Delivers A New Approach

Amazon initiates a new trend in supply chain management by handling 3PL (3rd Party Logistics) for its manufacturers in order to reduce the Time-To-Delivery (TTD) much shorter between manufacturers and consumers.

Today, most 3PLs are already hosting market place by providing logistics service at their distribution centers (DCs). Vendors and manufacturers are sending their goods to those DCs and the 3PLs handle the logistics for the vendors and manufacturers from those DCs. Amazon moves the 3PL services further to the “upstream” of its supply chain by moving the 3PL services from its DCs much closer to its manufacturers. This approach is quite different from Wal-Mart‘s logistics strategy, which is a centralized 3PL.

The benefit of the new distributed 3PL approach is worth watching. If you are interested in how to innovate your logistics operations, feel free to contact us.

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More iPhone 5c Supply Chain Rumors

More iPhone 5c Supply Chain Rumors

This article talks about a major challenge to supply chain planning. To have ample supply of iPhone 5s and 5c, how many does Apple need to plan and what is the production mix between the 2 models?

Steve Jobs‘ idea was to take the simple route by planning for one iPhone model only and focused on getting the best product to consumers. Tim Cook takes a different but traditional approach by introducing two models instead of one. He hope a cheaper model of 5c would attract more buyers, at least from the Asia. At least, this what the production plan tells us at the moment. The production plans for more 5c than 5s.

Contrary to what Tim expected, consumers would rather spend money buying the expense model 5s with new technology than buying the cheaper model 5c with previous generation of technology. This is why Apple needs to dramatically decrease 5c production and increase 5s production. This shows a supply chain planning mistake. It totally mis-calculates consumer demand by having a wrong product mix.

Check out this article for the challenges that Apple is facing and how we can help you to manage your supply chain.

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Consultants Should All Get Real Jobs

Consultants Should All Get Real Jobs

I challenge all consultants to spend some time — at least a year — back in a “real” job, working shoulder to shoulder with the same kinds of people who pay for their advice. So few authors and experts are willing to do this, because they’re afraid. They know it’s much harder to be accountable for a real team, in a real company, for a real project, than it is to critique and advise from the safety of the sidelines.

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Cloud Database for Dummies (Free E-Book)

Cloud Database for Dummies

Building a Database in the Cloud? E-Book Explains How.

It’s free for download as long as you have a free Oracle account.

Clear and concise, practical, filled with time-saving tips—the reviews are in on Building a Database Cloud for Dummies.

This quick-reference guide, organized into six short chapters and supplemented with helpful illustrations, provides a clear overview of the cloud and step-by-step instructions on deploying database as a service. Download the complimentary e-book today and learn how to:

  • Build a vision and business case for the cloud
  • Operate and deploy a database in the private cloud
  • Maximize success, with a list of the top 10 things to consider when starting

Cloud Database

Cloud database allow businesses to drive down costs while increasing business agility and IT performance. See for yourself how to save money, simplify management, and improve resource efficiency with a database cloud.

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