In the digital age, organizations as a whole and procurement departments in particular swim in data. It is everywhere, spread across an alphabet soup of internal and external systems – some connected, some not; some refined, some not; some structured, some not. It wasn’t always this way. Twenty-five years ago, the procurement function was manual, paper-based, and transaction-oriented. “Data” was but a character on Star Trek: The Next Generation. All of that has changed in the past 15 years, following the bubble and the wave of digitization, connectivity, and automation that has swept over the world. Now, “Big Data” permeates and drives the digital world, and it will only get more intense from here.

There is a Big Data “crisis” sweeping organizations and procurement teams today. But with the right people, processes, technologies, and ultimately the right attitude, this “crisis” can be an opportunity for Chief Procurement Officers (CPOs) and their teams to transform operations and deliver more value to the enterprise. Technologies exist today that allow procurement to not only manage Big Data up and down the source-to-settle value chain, but also leverage it for greater value.

This series explores further each of the eight sub processes of the source-to-settle process to illustrate just how Big Data can be managed and leveraged to make procurement’s life easier and extract the most value out of the data residing inside and outside of the enterprise. Next up, supply risk management.

What is Supply Risk Management? 

Supply risk management is the implementation of strategies to manage both every day and exceptional risks of supply based on continuous risk assessment with the objective of reducing vulnerability and ensuring continuity. It is not the elimination of risk, but rather the proper identification of it so that it can be weighed, evaluated, managed, mitigated, minimized, and/or accepted.

Supply Risk Management Resources and Tools

Procurement and supply management practitioners have a number of internal and external information sources at their disposal that, in their own way, help to paint a picture of an enterprise’s supply risk landscape. These include:

  • Spend analysis (as it relates to mission-critical categories, markets, regions, and suppliers)
  • Supplier data (i.e., supplier information, supplier performance)
  • Social-media information (trending topics or news – particularly controversial topics or news – as it relates to suppliers, regions, countries, or cities)
  • Third-party information services, which report on financial, geopolitical, market, and security matters. Common sources include Control Risks, Dun & Bradstreet, IHS Markit, LexisNexis, and StratFor. Other organizations, like the U.S. Central Intelligence Agency and the U.S. Department of State, provide country-specific data and analysis (The World Factbook, Travel Warnings and Alerts).

They also have several tools at their disposal to identify, score, evaluate, and manage supply risks. These include:

  • Heat maps, which show practitioners where risks are most prevalent across the globe. These can be broken down by country or region; category or supplier.Risk algorithms, which quantify and weigh risk factors, and aid in the modelling of supply risk scenarios
  • Risk models, which assign probability and impact under various scenarios and allow practitioners to “war game” risk scenarios
  • Risk sliders, which allow practitioners to adjust tolerances for certain risk factors that ultimately determine when a category, market, or supplier reaches critical status
  • Supplier management dashboards, which fuse internal and external supply and supplier data and allow practitioners to evaluate and manage risks in once place

How Do Source-to-Settle Solutions Manage and Leverage Supply Risk Data?

Like their supplier information and supplier performance brethren, supply risk management tools aggregate all of the disparate streams of supplier and supply information into one location and make it easier to manage. Any end-to-end solution will have a supplier management dashboard, perhaps even a dedicated supply risk management tool, that fuses all of the structured and unstructured data coming from across and outside of the enterprise, to paint a more holistic picture of the organization’s risk. Supply risk management tools can:

  • Pull in spend analysis – spend intelligence, really – that highlights category price trends and volatility, supplier value, and potential savings gaps (the difference between identified savings and realized savings) so that practitioners can realize when a given category, market, or supplier is putting their enterprise at risk.
  • Leverage supplier performance data, like scorecards and surveys, to help practitioners understand when a low- or non-performing supplier becomes a risk to the enterprise. For example, if the supplier is not adhering to contract terms and conditions, service-level agreements, or their quality is poor, then that information will be present within the dashboard – practitioners do not have to access a separate tool for it.
  • Tap social media feeds for real-time, tactical intelligence. Many dashboards link various social media streams – mainly, Twitter and Facebook – so that practitioners can “listen” to what consumers are saying about the enterprise and its suppliers. Enterprises can get ground-level views of operational and reputational risks this way, and leverage the power of social media to put “feet on the street” from across the globe.
  • Link third-party information sources that can provide practitioners with fact-based, specialized analysis of their supplier, market, country, or category. Although category and supply risk managers may know their categories and suppliers well, third-party information providers can round out their understanding of the target set, fill in gaps, validate, or even challenge the contemporary logic.
  • Quantify and qualify supply risks by aggregating and analyzing multiple data sources. Many social scientists love conducting mixed methodological studies because they present the best of both worlds: data-driven analysis backed up by nuanced explanations of the variables and their relationships. Supply risk management tools that effectively leverage Big Data do this by quantifying the risks and qualifying them with context so that practitioners can have a richer understanding of the risks and take thoughtful action.

Final Thoughts

Big Data has been a great windfall for supply risk management; but like any other part of the source-to-settle process, it can be overwhelming. Fortunately, there are solutions in the market today that can help teams ingest and digest information and turn it into actionable intelligence. By fusing and analyzing multiple streams of structured and unstructured data, modern supply risk management tools can enable small teams to conduct most of the heavy lifting of a large, dedicated supply risk management team. The resulting product can be produced with fewer hands and have greater fidelity than risk management processes done in an ad-hoc manner. For organizations that struggle to wrap their hands around supply risk information and be proactive, particularly small-to-mid-sized organizations, supplier management or supply risk management dashboards found within source-to-settle solution suites are prudent considerations.


How Source-to-Settle Solutions Manage (and Leverage) Big Data – Supplier Performance Management

How Source-to-Settle Solutions Manage (and Leverage) Big Data – Supplier Information Management

How Source-to-Settle Solutions Manage (and Leverage) Big Data – Contract Management

How Source-to-Settle Solutions Manage (and Leverage) Big Data – eSourcing

How Source-to-Settle Solutions Manage (and Leverage) Big Data – Spend Analysis

How Source-to-Settle Solutions Manage (and Leverage) Big Data – A Series Introduction

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