Category Archives: Knowledge Management

Take the First Step on Your Next Level Supply Management Journey

And start by downloading the new BravoSolution sponsored Sourcing Innovation WhitePaper on “Taking the First Step on Your Next Supply Management Journey” [registration required] today!

Lamenting that the acronyms and acclamations are flying fast and furious in the Supply Management space, with phrases like VFS. Hi-Def Sourcing. Next Level Supply Management. Next Practices. leading the way, this paper, which notes that even world class Supply Management organizations have to do something more to maintain their year-over-year contributions to the bottom line with the perfect Procurement storm of high demand, low supply, and high market volatility brewing off of the coast, provides a roadmap for those Supply Management organizations that are looking to begin, or continue, a Next Level Supply Management Journey.

For an average organization, this will be a long journey that could take the better part of a decade. There’s a reason that only 8% of the Procurement organizations make the best-in-class cut (defined as being in the top quartile of both efficiency and effectiveness) in the Hackett Group rankings (which benchmark 73% of the Fortune 100). It’s tough to be the best. (But not out of reach for the dedicated. That’s why the rankings change year over year.)

In order to help a Supply Management organization begin its Next Level journey, this paper starts by defining a 3-Level Maturity Model across nine axes that can be easily understood by any Supply Management organization. While you can argue for 5 (and follow the Hackett Model), or even 7 (and follow a pyramidal model), by breaking the model down at the borders, the reality for most organizations is that they are either are best in class, better than average, or worse than average, and until they are deep in a journey, any classification that is more fine-grained just confuses the issue.

The nine axes are:

  • Sourcing Process
  • Organization
  • Finance
  • IT
  • Product Management & Marketing
  • Risk Management
  • Asset Management
  • Relationships
  • Metrics

And depending on where you fall on the majority of these metrics, this will slot you either into a

  1. st level organization still in the standardization and complexity reduction stage, a
  2. nd level organization in the operational excellence stage of Supply Management, or a
  3. rd level best-in-class organization that has progressed to the head of the pack with its mastery of strategic business enablement.

To find out where you fall, and get some good ideas on how you get there, download the BravoSolution sponsored Sourcing Innovation white-paper on “Taking the First Step on Your Next Supply Management Journey” [registration required] today!

A Digital Transformation Requires At Least Five Critical Factors, Not Three!

A recent article over on Chief Executive on Digital Transformation that asked “[If] CEOs [are] ready for the Challenge?” caught my attention. And it kept it when it said less than 20% of the companies surveyed are truly reshaping their businesses for digital and many are only partially fulfilling their potential because, as a technophile, I know this to be all too true.

But I screamed NOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO with @rantinggirl when I read that you need three factors in place — top-down vision, clear governance and investment — to deliver a true transformation. While these factors are a necessary condition, they are not a sufficient condition, and if all you have is vision, a governance model, and the willingness to invest current resources into the problem, then you should pack it in now as your days as an organization are numbered.

You see, a successful digital transformation requires at least the following Five Critical Factors:

  1. Top-Down Vision
    that emanates from, is communicated by, and is embraced by the top
  2. Clear Governance
    that consistently communicates and enforces the vision, ensures the allocated resources are directed towards the effort, and that keeps the vision on track when fires threaten to cloud the business with smoke or people want to return to the old ways
  3. Investment
    in resources and dollars, as money will need to be spent requiring the right infrastructure
  4. Technologically Adept Talent
    since going digital requires being digital
  5. Transition Commitment
    since there will always be those that fight the transformation and, more importantly, since some of these resources may not be able, or willing, to adopt to the new way of doing business and have to be let go

Anything less is like skydiving without a properly packed parachute. You had a clear vision of jumping out of the plane, you invested in the plane, and you convinced the pilot to take off, but you forgot about the nature of the landing and that if the chute doesn’t properly deploy, you’ll be hitting the ground at 195 km/h (or 122 mph) — without much chance of survival. Mr. Boole may have survived, but chances are you’ll end up like the skydivers on CSI.

As the article points out, the transformation journey is full of roadblocks, including organizational skill gaps, culture, and legacy IT (that is more antisocial than your average arrogant PhD, and I should know).

EQ does not matter more than IQ — Nice to see not everyone is getting caught up in the hype!

EQ, short for Emotional Quotient and also known as EI, short for Emotional Intelligence, and the next resurgent craze in talent management, is very important in Supply Management given the regularity with which supply management professionals need to interact with suppliers and peers around the globe, the number of disruptions that occur on a semi-annual basis, and the intra- and inter-organizational conflicts they will be regularly called in to resolve. After all, people with high EI have more empathy, tend to stay calm under pressure, and have a knack for effectively solving conflict.

But, despite what Daniel Goleman may have claimed back in 1995 (when he authored a book titled Emotional Intelligence: Why it can matter more than IQ), it does not matter more than IQ. As Zoe Lewis, a director at Harvard Lewis, notes in this piece in CPO Agenda on how “clever is no longer enough”, EI must complement IQ. EI and IQ have equal value and it’s equally important for leaders to have a high IQ because in that position they need to be able to make certain decision. You can be the most motivated, empathic, and socially adept individual in the world, but if you don’t understand a balance sheet, ROI, or even the basics of a production line, there is no way you are going to effectively lead a manufacturing organization — or even make any important decision in its day to day management.

In Supply Management, IQ is just as important as it is in senior leadership. In order to be successful today, a Supply Management professional has to be a master of transition and technology — that includes Spend Analysis, Decision Optimization, and Predictive Analytic Demand Planning Solutions. That requires some serious IQ to understand not only how to use the tools, but what patterns to look for, what models to build, and what statistical and interpolative techniques are appropriate for the categories and commodities being sourced. You can be the most emotionally intelligent man, or woman, in the world and be perfect company for Jonathan Goldsmith, but if you don’t understand how to navigate a spend cube, breakdown costs into raw components acceptable to an optimization solution that uses a piecewise linear mixed integer programming model, or understand the difference between statistical interpolation and comparative pattern matching, well, let’s just say that there’s hundreds of thousands in technology purchases and licenses down the drain.

Of course, it is EQ that makes the difference between a good buyer and a great buyer as the dynamics of the position will continue to change much more along the way of relationship management. This is primarily because the need to reduce costs today is as dire as it ever was and traditional methods of working with suppliers and stakeholders only achieve 3% to 4% improvement a year — not the 30% to 40% improvement targets now placed on some buyers. Even spend analysis and decision optimization, the only two technologies in supply management proven to deliver year-over-year returns in the double digits (at 11% and 12% respectively), will not come close to these targets. Only collaborative sourcing techniques that utilize these technologies as part of joint efforts with suppliers to identify opportunities for significant cost reductions (which take major EQ as well as IQ to pull off) have a chance of delivering those returns.

And the good thing about EQ is that, unlike IQ, it can be improved over time. While you generally realize your IQ potential early on in your life, with effort, your EQ can keep increasing. Even if you start of with no social skills and are outcast like a Napoleon Dynamite, if your IQ is smart enough, you can still become a James Bond, or at least an Alastair Donald, who is a secret agent of business improvement. Once you develop self awareness, self-regulation, social skills, and eventually empathy can follow if your motivation, and patience, is strong enough. You can take self-assessments, courses, or get a mentor. It may not happen over night, but you can get there.

And you can get there faster if your organization makes the move from a training organization, where lessons are forgotten as soon as the next fad is brought in by senior management, to a learning organization where best-in-class methodologies, that are really only best-in-class for your competitor, are not force-fed from the top but developed bottom-up by motivated, engaged employees who want to make the organization a better place to work and share what they learn. That’s the foundation for true EQ in an organization.

Good Data Will Not Guarantee Good Decisions … But Informed Skeptics Increase the Odds

In our last post, we noted how great it was to see this recent article in the Harvard Business Review on how Good Data Won’t Guarantee Good Decisions because investments in analytics can be useless, even harmful, unless employees can incorporate that data into complex decision making and only 38% of employees and 50% of senior managers, on average, are equipped to make good decisions given good data. As pointed out by the authors, there are too many “unquestioning empiricists” and “visceral decision makers” and not enough “informed skeptics” who can effectively balance judgment and analysis with strong analytic skills and a willingness to listen to others’ opinions, but dissent if necessary.

As a result, organizations need to do whatever they can to increase the number of informed skeptics within their four walls. So what can they do? According to the authors, they can:

  • Train workers to increase data literacy
    and more efficiently incorporate information into decision making so they can make better decisions and
  • Give the workers the right tools
    to turn the data into information.

With respect to training, the authors recommend workshops and coaching. Workshops can teach them that they must understand the factors and calculations behind the numbers and learn to think critically about the accuracy, sample sizes, biases, and quality of their data. Even people who took statistics in college could probably use a refresher to help them apply what they learned then to their current jobs … especially since most people, analysts included, don’t understand statistics. (Remember that there are lies, damn lies, and statistics.) Coaching by people-oriented data experts can provide informal, ongoing training to employees that can gradually improve their skills. Given that surveys indicate that only 25% of all knowledge workers receive effective training in information analysis and use, this is a good start.

With respect to tools, there is a vital need to interpret data displays in a manner that allows them to deduce the information the data contains. Just because most executives choose to go with good-enough data now vs. perfect data later doesn’t mean it’s the right thing, not because perfect data is always a useful goal (as sometimes good enough is good enough), but because, without the right tools and understanding, it’s not always clear if good enough is good enough.

But is this enough?

No.

Three factors are always required for success: technology (tools), talent (training), and transition (change management of the process). Overlooking how the training is to be applied, the technology is to be used, how the results are going to be interpreted, and how the change from dumb data to intelligent information is going to be implemented so that it sticks, the training takes hold, the technology gets used, and the results get repeated is very important. Otherwise, a few moderate wins will be made, but as pressure mounts to get things done, the talent will revert to the old ways and the tools and training will be for nought.

Good Data Will Not Guarantee Good Decisions

It was great to see this recent article in the Harvard Business Review on how “Good Data Won’t Guarantee Good Decisions” now that we are in the age of “Big Data” (which, in business, is Bullshit in Guise) and everyone is diving into their OLAP and reporting tools without even a clue as to what they are (or should be) looking for. There’s data. There’s information. There’s knowledge. There’s the intelligence required to understand it. And then there’s the wisdom to choose the right course of action.

As the authors state, investments in analytics can be useless, even harmful, unless employees can incorporate that data into complex decision making.

In the article, the authors summarized the result of a study by the Corporate Executive Board that evaluated 5,000 employees at 22 global companies. The study separated the employees into three groups:

  • Unquestioning Empiricists
    who trust analysis over judgment
  • Visceral Decision Makers
    that go exclusively with their gut and
  • Informed Skeptics
    who effectively balance judgment and analysis with their strong analytic skills and willingness to listen to others’ opinions but dissent.

Only the latter group are equipped to make good decisions, and, not unexpectedly, only 38% of employees and 50% of senior managers fall into this group.

And when you consider that their analysis also found that the functions where the employees had the highest average scores performed 24% better than other functions across a wide range of metrics (including effectiveness, productivity, employee engagement, and market-share growth), this is not a good thing.

Why is this the case? The researchers identified the following four problems that prevent organizations from realizing better returns on their data investment:

  • analytic skills are concentrated in too few employees
    just because you have a few experts doesn’t mean that the analytics skills will trickle down
  • IT spends too much time on “T” and not enough on “I”
    IT is used to working with functions where business needs are clearly defined, stable, and relatively consistent … when the needs become less defined, IT becomes less able to support them
  • reliable information is hard to locate
    many organizations lack a coherent, accessible structure for the data they’ve collected; the authors found in their survey that fewer than 44% of employees say they know where to find the information they need for their day-to-day work
  • business executives don’t manage information well
    (at least when compared to capital and brand) — they focus on more physical or traditional assets

While not addressed, and possibly not covered, by the study, I’d also add the following to the list:

  • No Good Roadmaps Exist
    Analytics skills are not enough — a guide on how to find the needle in the haystack is also required; take Spend Analysis for example … how many practical guides exist? (At least one.)
  • Lack of EQ
    as an employee needs to not only understand where to look, but when something is worthwhile to chase and when it’s not as there is a need to understand the business impact of what the data might be suggesting which requires understanding the business needs as well as the data

So what can an organization do to get more informed skeptics?