Category Archives: Spend Analysis

Maverick Spend is Good. Wait, What?

For years and years and years the doctor, the maverick, and every other thought leader in Procurement have collectively been telling you that maverick spend is bad. It erodes negotiated savings, builds mistrust in the supply base, and underlies your Procurement processes. It encourages rogue behaviour and increases the organization’s exposure to risk and liability. Good Procurement is not accomplished by loner hot-shots, but an integrated, dedicated team that manages the supply chain end-to-end and makes sure the entire chain is strong, not just one link.

But, sometimes, if approached in the proper manner, Maverick spend can be good. Maverick spend can help you identify weak processes, better products and services, preferred suppliers, and even poor definitions of on-contract and off-contract spend. Even though it’s still bad if the buyer is buying off-contract, paying more than needed, risking good supplier relationships, and potentially exposing the organization to compliance and liability issues, maverick spend still presents an opportunity to improve Procurement processes, procured products, and even personnel.

How? Check out the new Spend Matters Pro Piece in the maverick‘s 50 Shades of Pay series that was co-authored by the doctor on “Maverick Spend Analysis: How to Re-Plumb Your Spend and Savings Flow” and find out how you can knock your spend analysis success up a notch, even if you don’t have a spice weasel.

The Boxing Day Blogger’s Lament

Sorrow is my own yard
where the new grass
flames as it has flamed
often before, but not
with the cold fire
that closes round me this year.

For five straight years
On this day we spend rapped.
The web page is white today
no insights from grey beards.
Insights on spending
once filled many pages
put colour in our cheeks.

Yellow and some red,
but the grief in my heart
is stronger than they,
for though they were my joy
formerly, today they are absent
and we do miss old grey beard.

Today a bird told me
that in the meadows,
at the edge of the heavy woods
in the distance, he saw
a glimpse of grey beard.
I feel that I would like
to know that
the old grey beard will return
and bring us a spend rap again.

Procurement Trend #06. Data-Based Predictive Analytics

Three annoying anti-trends remain. We’re so close to the end that we can almost taste the bitter-sweet victory, but the sour taste in our mouths still remains as we must continue to provide those fashionably-challenged futurists with counter-examples to the trends of their fore-fathers that no one who didn’t lock themselves in a windowless padded room would try to pass off as a trend of tomorrow. We want to shame them for their stupidity, but we will leave their hard-earned humiliation for LOLCat, who is obviously quite fed up at having to spend yet another life listening to their ludicrousness, but still finding the time to point out how LOLCats have been sustainable at least since the first corrugated cardboard box was created.

So why do these pit-dwelling prophets from Hawalius keep pushing us trends from the rubbish pile? Besides the fact that some of them obviously spent the best part of last decade in a rancid cave, probably because they look around, see the laggard organizations still struggling with last decade’s technology, and assume they can still sell last decade’s leftover snake oil in today’s marketplace. Thus, if most organizations are struggling with proper historical spend analysis, data-based predictive analytics is obviously a future trend, and

  • good decisions require good data

    and so few organizations have good data

  • inventory forecasting is getting harder and harder

    as sudden changes in unemployment rate, interest rates, and brand sentiment as well as unexpected supply chain delays or competitive product introductions can all have a large impact on demand

  • market prices are getting even harder to predict in volatile markets

    and profitability often depends on slim margins

Which would be great reasoning if leading organizations hadn’t figured this out over a decade ago and moved on to doing something about it a while ago!

So what does this mean to you?

Clean and Enrich Your (Master) Data

Dirty data dictates dastardly decisions. And those never end well. But don’t go crazy trying to do it. 100% clean data is a pipe dream, and, as with most situations, the 80/20, or, to be more precise, the 90/10 rule applies. Clean and enrich as required to confidently map 90%+ of spend, including 90%+ of the spend for the top 90%+ of suppliers and the top 90%+ of products. Stop when the effort exceeds the return. With a good mapping tool, the mapping can be done for even the largest Fortune 500 by hand in a week. Depending on how good the data is, the analyst might even get to 95% or even 98%. Then, identify any glaring weaknesses (such as supplier financial or risk data, market data, or cost breakdowns relative to a Bill of Material) that are important from a spend analysis or should cost modelling viewpoint, and get that data.

Put Protocols and Safeguards in Place to Keep your (Master) Data that Way

It’s going to take time, money, and manpower to map, clean, and enrich the data. This will be time, money, and manpower wasted if protocols aren’t put in place to make sure not just anyone can update master data, or at least not without review and verification. Put workflows and approvals in place to minimize the chances of bad data getting into the system or data getting out of whack too quickly.

Automatically Augment Your (Master) Data with Market Data

Good historical data is good. But current market data is better. With past and current data you can not only know current conditions, but with current market data, updated regularly, you can compute trends.

Use All the Data to Predict Trends and Make Sourcing Decisions

Use the computed trends to predict likely future conditions based upon the trends and current market movements. Based on this data, you can judge whether or not it is a good time to source a category and lock in long-term pricing.

Optimize, don’t Compromise!

Continuing on our theme of analysis and optimization, every e-Sourcing suite on the market will support your organization in its sourcing activities, but not every product will allow your organization to optimize it’s sourcing activities.

Optimization requires advanced sourcing capability, and advanced sourcing requires the ability to analyze data, not just collect and report on data.

This means, that at the very least, you will require:

  • true spend analysis,
  • true category analysis,
  • true cost-based bidding, and/or
  • true bid optimization.

Without at least one of these capabilities, you’ll never optimize your spend. So don’t even both to try without them.

If I Succeed in Destroying Dashboards and Razing Report Writers, What Next?

In yesterday’s post, where I responded to the smart alecks, I noted that, once dashboards are destroyed and report writers are razed, there was about a half-dozen next logical steps that could be taken to improve today’s spend analysis solutions, even if that solution was BIQ.

Should cost modelling, award optimization based on historical data and business rules, and federation across related data sets for deeper dives are pretty obvious. Are there somewhat less obvious advancements we should also be thinking of?

Of course. One rung up the ladder, three of them are:

Predictive Modelling

Once you have should-cost modelling, the next logical step is predictive modelling. Use historical data to extract pricing trends and predict likely future prices for the commodity. Use this to determine not only the best time to (re) source the category as well as using deep-dive analysis to determine the best strategy.

Optimize Supplier Relationships

Once you have optimized all of the awards based on historical data and business rules, you also have the optimal allocation by supplier. Once you have the optimized set of awards for each supplier, you can optimize the re-order schedule, shipping arrangements, and even production and sourcing schedules on behalf of the suppliers and take costs out one level down in the supplier chain. Helping your suppliers help you goes a long way to building good supplier relationships and increasing supplier performance.

Simultaneous Drill Across Multiple Data Sets

Once you have true federation, you want to split the screen and update the views to only contain the relevant data in each data set as you drill down through the data. Going back to our previous example, you start in the Payment cube drilling into the goods receipts associated with the wonky widgets, then switch to the Order History cube to find the initial requisitions, but when you drill on the user in the second cube, the first cube is updated to contain only those goods receipts associated with the user. The user can drill through either cube to find the data she wants, whichever is easiest, and both cubes update. She doesn’t have to go back and forth.

These are just a few more things that can be done, and all would simplify the life of an analyst. More to come at a later time but first, this time I’m going to insist that you tell me what you would do. :-;