Online Exclusive: The Benefits of Supply Chain Organizations

A new book is a demystifying primer and a must-read for all supply chain professionals.

Written by Francis X. Murphy, CPIM, CSCP, SAP – P2P consultant, Estée Lauder Companies Inc.

In regard to Supply Chain, we glibly sing the praises of “Two-way information flows,” “End-to-end Visibility” and “Collaborative Decision Making.” All too often we brush past the workhorse that enables these good things.

That workhorse is Analytics. And we brush past it because it conjures up images of brainiac mathematicians and their handmaidens in I.T., spouting the virtues of “linear regression analysis” and “probability distributions.”

However, to truly realize the benefits of the Supply Chain, organizations must embrace Analytics as the enabler. The book, Analytics at Work: Smarter Decisions / Better Results, by Thomas H. Davenport, Jeanne G. Harris and Robert Morison, is a demystifying primer and a must read for all Supply Chain professionals.

Their engaging deconstruction makes the subject amazingly approachable for non-technological schmoes of any stripe. Yet it maintains sufficient investigative rigor to pass muster with PhD technocrats and self-taught “data hogs.”

Right out of the box they define Analytics through the prism of human beings driving technology (rather than the inverse). While the mantra is to collect more data to become more fact based in decision-making, they give ample nod to the value of intuitive methods. Here’s an example of their insight and engaging style:

“Oh, yes, we’ve got lots of that (Analytics) in modern airliners – avionics, lots of computers, ‘fly by wire,’ and all that. But I still occasionally find it useful to look out the window.” (anonymous pilot)
However, they are quick to balance by paraphrasing the wisdom of Socrates, “…the unexamined decision is not worth making.”

So we come to understand that victory requires the 10,000 ft vision but we martial the troops to win battles and minimize casualties with facts on the ground. And fact-based decision making is the essence of Analytics.

The authors point out that every organization needs to answer fundamental questions about its business and that, “Taking an analytical approach begins with anticipating how information will be used to address common questions.” They offer us a schematic aligning the known (Information) with potential discoveries (Insights):

Past and Present information is harvested from traditional business reporting. Applying “rules” enables alerts for undesired performance as well as extrapolating forecasted behavior from past trends. By applying analytical tools (e.g., statistical modeling, optimization, etc.) we move beyond simple information/reaction to insights/proactive decisioning. Taking this leap gives a much deeper understanding of a business’s dynamics.

Embracing Analytics will prove transformative to most organizations. so Davenport, Harris and Morison organize their early chapters around the acronym DELTA to represent critical concepts:

• DATA – The Prerequisite for Everything Analytical
• ENTERPRISE – Integrating Across Organizational Silos
• LEADERSHIP – The Deciding DELTA factor
• TARGETS – Picking Your Spots for Analytics
• ANALYSTS – Managing Scarce and Valuable Resources

Their later chapters wrap around acknowledging the hard work challenges of embedding and sustaining Analytics into an organization. They also present real world success narratives (eBay, UPS, Carnival Cruises, Best Buy and even actor Will Smith).

Analytics, similar to Supply Chain, is an evolutionary process. The authors segment Analytics into five phases of maturity. Supply Chain professionals will see a correlation between our growth phases (Multiple Dysfunctional, Semi-functional Enterprise, Integrated Enterprise, Extended Enterprise) and the following:


1. Analytically Impaired – Lacking one or more prerequisite: Data, Skill sets, Executive Management Champion
2. Localized Analytics – Departmental silos developing analytics with their own data. There are no cross-functional projects focused on company strategic targets
3. Analytical Aspirations – The company establishes analytical capabilities, initiates a few significant projects and envisions a more analytical future. Progress is slow because some DELTA factor is difficult to implement.
4. Analytical Companies – Human and technological resources are in place, analytics applied regularly, and benefits realized across the enterprise. Strategic focus not yet grounded on analytics and analytics not turned into a competitive advantage
5. Analytic Competitor – The company routinely uses analytics as a distinctive business capability. It takes an enterprise-wide approach, has committed and involved leadership, and has achieved large-scale results. It portrays itself both internally and externally as an analytical competitor.

The stated intention of the authors is to present a “how-to” guide to introduce fact-based decision making and realize Analytics as a competitive advantage. They effectively achieve this by periodically overlaying their DELTA concepts to their MATURITY STAGES. This provides business professionals a matrix of plain spoken steps to manage transitions. For example, to transition from Analytically Impaired to Localized Analytics you need to do the following to your DATA:

“Gain mastery over local data of importance, including building functional data marts.”

To transition from an Analytical Company to an Analytic Competitor requires the following LEADERSHIP:
“Encourage leaders to be visible with their analytical capabilities, and to communicate with internal and external stakeholders about how analytics contribute to success.”

Getting an organization started down the path of being analytical requires a bit of selling and the authors speak to this in “TARGETS – Picking Your Spots for Analytics.” They suggest selecting an area with a ‘data rich environment’ and ‘measurable goals’ (sounds like Supply Chain to me). They offer the construct of a “Ladder of analytical applications” where one step builds upon another. The rungs in ascending order are: Data in order, Key targets/segments, Differentiated action, Predictive action, Institutional action, and Real Time Optimization.


The concept, “ANALYSTS – Managing Scarce and Valuable Resources” presents a hierarchy of talents and reinforces the notion that analytics is appropriate to all roles and levels across the enterprise. We are presented four profile types: Analytical Champion, Analytical Professional, Analytical Semiprofessional and Analytical Amateur.

We are also presented with four skill sets: Quantitative and Technical, Business Knowledge and Design, Relationship and Consulting, and Coaching/Staff Development.

Here, again, the authors create a matrix, this time pointing to a potential analytic aspect for all roles and levels in a company:

At the executive level, Supply Chain will be Champions. At the adoption and execution level, Supply Chain folks will be Semi-Professionals. This comports with our classic role as facilitator between I.T. developers (Professionals) and the user community (Amateur). Note how the Professionals are heavy on “Quantitative” but light on “Relationship and consulting.”

True to their intention, giving us a “how to” manual for Analytics; Davenport, Harris and Morison conclude with a passage “What We Promise and What We Don’t.” They offer up caveats, “Analytical decisions aren’t the only ones that will lead to success…Analytics are not all you need to make good decisions” acknowledging we cannot discount the value of business experience and market knowledge. They also caution what has happened in the past is not always a predictor for the future.

However, the relentless review of data for trends and variations of “outcomes versus plan,” will absolutely lead to better strategic decisions, improve processes and accelerate responses with consistent results.

Analytics at Work: Smarter Decisions/Better Results absolutely deserves a spot in every forward thinking company’s Supply Chain library.