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Sustainable Results

2015: Thinking… Smarter, and Supply Chain Best Practices

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Thinking… smarter.  Perhaps a mantra for 2015? We unquestionably think so.

Supply Chain best practices evolve continually, based on emerging technology, global expansion, economic activity, progression of IT platforms and network architecture, and, well the list goes on.

So, with the onset of a New Year, it is perhaps time to think smarter and visit the best practices for global supply chains.  Let’s begin with two of our favorites,  data analytics and tail-end spend.

Data Analytics

Simply put, data analytics is the science of examining raw data with the purpose of drawing conclusions about that information. Managing big data can be daunting to say the least. But, the many enterprise benefits realized by implementing this relatively new science significantly outweigh ignoring the gems hidden in your corporate data.  This practice of enhancing decision-making by probing data to uncover real-time insights has become so pervasive that universities across the globe are rapidly incorporating this science into their curriculum.

Even Hollywood recognizes the crucial role analytics can play… in winning wars. Benedict Cumberbatch, nominated for a Golden Globe for his role the The Imitation Game , plays code-breaker Alan Turing, who greatly contributed to ending World War II by analyzing and deciphering billions of Nazi Germany code combinations.

The supply chain has several valuable uses for analysis as well.

Fraud. Not necessarily easy to detect, but repetitively incremental cases of fraud can relentlessly impact the bottom line. For example, volumes of purchases below a lower clip level can go undetected for months or years without diligent analysis. Discovering spikes in buying patterns can uncover fraudulent spend.  Duplicate invoicing, whereby suppliers may inadvertently issue multiple invoices for one purchase order, may not be identified unless appropriate controls are in place.

In fact, Forbes Magazine recently cited a Deloitte Financial Services study in which 2,600 executives were polled concerning their data-analytics tool usage. “The study found that fewer than a third of respondents were deploying the kind of data-analytics tools that can detect fraud or waste by vendors. Another 13% had the necessary tools but were still learning to use them, while 22% had no data analytics of any kind.”  That leaves many supply chains vulnerable to deception.

SDI’s deploys a series of analytics best practices. Our spend analysis alone allows us to classify spend per managed category, resulting in profitability, reduced cycle times, improved compliance with KPIs and sustainable, socially-responsible outsourced programs.

Managing Tail-end Spend

A primer, for those not intimately familiar with tail-end spend.  Essentially, we can use the old 80/20 rule to help explain.  Procurement operations typically focus vigorously – and rightfully so – on their “core” or “strategic” spend which, roughly speaking, might comprise 80 percent of an enterprise’s procurement budget. But who is minding the remaining 20 percent of spend that some consider – but shouldn’t – inconsequential?

Therein lies the problem.

Many companies maintain large numbers of non-strategic / non-core suppliers, with high volumes of low-dollar, non-critical spend. These purchases from non-critical suppliers often lack governance and visibility. Furthermore, they are neither centralized nor standardized.

Supply Management, a purchasing and supply website, recently stated what SDI has been passionate about – and practicing –  for years: “Procurement teams invest heavily in their core spend areas, but the final 20 per cent of spend, the “tail-end”, remains a largely untapped opportunity for most companies.”

At SDI, we centralize procurement operations, standardize systems on a single common platform for all suppliers, and Implement rigorous process controls.

Are there only two best practices? Not quite.  Stay tuned for visibility and compliance… with, perhaps, a dash of risk mitigation.

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