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20 Analytics Predictions from the “Experts” for 2020 Part II

In our last post we started reviewing 20 analytics predictions being peddled by the major analytics futurists and analytics sites. Why? Because while overly optimistic futurist authors rarely get it right, their predictions do point out two things. What should be done — and isn’t getting done — and where the space needs to go.

And even though 19 of these anti-predictions won’t (fully) come to pass this year, we started reviewing them one by one to give you a reality and indicate what is likely coming sooner than later, and what is still a pipe dream. Most of the predictions we reviewed yesterday were those that fell into the “aren’t happening” or “aren’t really happening at all” (because they are more of the same old, same old) buckets, but today we get to some that will start to materialize and the one, yes one, that is 100% true — and that you need to be fully aware of.

So settle in and let’s finish this.

AI becomes more mainstream

Well, acceptance of AI will continue to become more mainstream, but considering that most “AI” providers are actually providers of “Artificial Indirection” and have no AI at all, not even at the level of “Assisted Intelligence”. Most providers of “AI” are just providers of RPA (robotic process automation) at-best, and a configurable rules-engine at worst.

Multi-hybrid

A few vendors are offering multi-hybrid analytics solutions, and a few more will, but there will be nothing new. It will be one solution for integrated in-platform analytics, another for do-it-yourself analytics, and possibly an in-house developed third for database management and cube construction. But there’s going to be no significant changes here — most practitioners are going to use what their vendors give them.

Analytics will become usable by business analysts

Well, this one is half true. With recent advances in user interfaces and usability, it will become more usable … but … only to the better half of the business analysts … and … only with training. And this is where this particular prediction fails. Training has been high on the priority list for a decade, and it’s also been high on the “cut when budgets need trimming” list for a decade as well. There will be little to no training as per the norm, so only the most dedicated will self-learn and use it.

Data governance takes centre stage

This prediction is likely to come sooner than you might think, but not in 2020. Until there is a big cost associated with the lack of data governance, like training, it’s going to remain high on the priority list but not going to get centre stage. This will only change when lack of governance risks a huge fine or a large organization loses a major court case with a large judgement that was the result of lack of governance (which resulted in data exposure) which could have happened to any governance.

AI ethics standards will emerge

We all wish this will happen, but as with data governance, until a large organization loses a discriminatory court case as a result of an AI decision, and the court holds the organization responsible for that AI decision, no one is going to put any real effort, beyond lip service, into AI ethics. At least from a vendor perspective. A few lawyers hungry to make a name for themselves might, but that’s about it.

Analytics will hit the C-Suite

Re-set the woody woodpecker laugh track. If the average business analyst is not going to get much more involved with analytics, then you can bet the average C-Suite executive is not going to get much more involved either. They might get better reports and dashboards, but that’s it.

Intelligent assistants that connect the dots will become more pervasive

This is another half-truth. “Intelligent assistants” that allow a user to interact with the application in natural language, and especially English, will continue to infiltrate S2P platforms, but as to connecting-the-dots … not likely. That will require true embedded machine learning technology, and that’s still far away for the average provider.

Open source is going down the drain thanks to cloud platforms

This is yet another half-truth. While it is true that as more and more providers lock into a cloud platform (such as Azure, Microsoft, and Google) they will lock into whatever analytics are provided in the platform, this is not going to stop open source efforts — although uptake may trickle off for a while.

Effective implementation will continue to be a challenge

This is mostly true. Effective implementation will continue to be a challenge for the majority of organizations, and only a few best-of-breed providers will see the challenge of effective implementations decrease. As data continues to proliferate, especially considering the average quality of data, analytics will continue to get more challenging on the whole.

And now, finally, the one prediction the doctor found that is 100% accurate.

Companies will continue failing analytics & AI transformations

This is absolutely true. Considering that analytics requires good data and AI requires lots of good data, good algorithms, and experts to guide the algorithms, and most companies have poor data, poorer algorithms, and a dearth of experts … and often rely on vendors who peddle applied indirection, the doctor expects a big uptick in failures until the space educates themselves on what AI truly is, what the levels are, what is actually out there, and who is actually offering it.

For details on what the levels are, and what is coming, keep your eyes on SI and SM, and if your organization has been smart enough to subscribe, check out the doctor‘s pieces over on Spend Matters Pro on AI in Supplier Discovery, Sourcing, Optimization, Procurement, and Supplier Management.

AI in Procurement: [Spend Matters Pro subscription required]
Today Part I,
Today Part II
Tomorrow Part I,
Tomorrow Part II,
Tomorrow Part III
The Day After

AI in Sourcing: [Spend Matters Pro subscription required]
Today
Tomorrow Part I,
Tomorrow Part II
The Day After

AI in Sourcing Optimization: [Spend Matters Pro subscription required]
Today
Tomorrow
The Day After Part I,
The Day After Part II

AI in Supplier Discovery: [Spend Matters Pro subscription required]
Today
Tomorrow
The Day After

AI in Supplier Management: [Spend Matters Pro subscription required]
Today Part I,
Today Part II
Tomorrow Part I,
Tomorrow Part II
The Day After

How Do You Know If That SaaS is Priced Right?

As per our recent post on What is that Platform Worth?, SaaS is good, but only if you get an RoI from the subscription license fee. So how do you know if that SaaS platform is priced right for you?

Six years ago we ran a post on Good SaaS vs. Bad SaaS where we focused on some of the key non-functional characteristics that should be examined in your SaaS purchase process. Six years have past, and they still haven’t really changed. In summary,

Good SaaS is Bad SaaS is
focussed on value sold on cost
has RoI models and plans to achieve them talks about process improvements and associated cost reductions
is designed to support business cases is focused on manpower reduction
has offerings and prices applicable to different customer sizes has a one-size-fits-all offering and pricing scheme
competitively priced for what you need priced out of the ballpark

Breaking it down, a good SaaS vendor comes in with a proposal that

  • competitively prices the solution based upon a value model that
  • demonstrates a realistic realizable ROI based upon an
  • appropriate implementation plan that not only addresses
  • process and workflow improvements that will result not only in manpower reduction and cost reductions but
  • increased throughput and improvements that will increase the overall value Procurement contributes to the organization.
  • And the vendor will be able to help you summarize all of this in a business case customized for your organization.

    It’s about your needs, not their optimal sales process / price-point.

Purchasing Blues (Repost)

It’s the first day of summer, so:

Click Here to sing along!

Well, it’s time to raise a fuss
and it’s time to raise a holler
About diminishing returns
from the corporate dollar
I just heard from my boss
who governs me
If I don’t save the cash
he’s gonna fire me

Sometimes I wonder
What I’m gonna do
If there ain’t no cure
For the purchasing blues

The buyer he told me to
go beat on the supplier
That his margins must be high
with ours under the wire
So I talked to the supplier
he said that costs were elevated
He was losing all his money
at the rates we had created

Sometimes I wonder
What I’m gonna do
If there ain’t no cure
For the purchasing blues

So I found a consultant
told her ’bout my problems
She discovered that
the supplier was just stalling
Material costs were falling
and the exchange rate was fair
I had wasted all my time
just pulling out my hair

Next time I have a problem
I’ll find me a solution
I’ll find a sourcing expert
and get my retribution

No more will I wonder
What I’m a-gonna do
I’ll find me a cure
For the purchasing blues

Sourcing Talent is Rare

Sourcing, like many facets of Supply Management, is not as easy as it seems. The skills required to identify the products and services required, identify potential suppliers, construct an appropriate RFI, evaluate that RFI, construct an appropriate RFP, evaluate that RFP, identify suppliers for negotiations/RFQ, assess the market, assess the RFQ responses against the market, select one or more finalists, negotiate, define the award, create a contract, and manage the whole process are quite numerous. Especially since that’s just the basic process. A determination of demand, of current market conditions, of expected cost, etc. will require spend analysis, (should-cost) modelling, and (statistical) trend projection. If multiple bids are competitive, and an auction is out of the question, then (strategic sourcing) decision optimization, and the mathematical modelling it entails, is also required. Plus, if the buy is strategic, then multiple stakeholders will be involved and cross-functional team-management skills will also be required. All this, and more, may be required just to get to a contract.

Then comes the actual Procurement. This will involve considerable skills in logistics, inventory, and global trade. When do you place the order? What is the best mode of transportation? Do you cross-dock or not? If the inventory is available too early, do you store it over-seas, before export, or locally, after import. If there are value-add components, do you take them or leave them, as they can considerably increase import or export tariffs? For example, sometimes the difference between shipping a cartridge in a printer and shipping it separately will save a few percentage points off of the total cost. (Check the HTS codes if you don’t agree.)

So, to re-iterate, you need the following skills at a minimum:

  • (Cost) Analysis / Market Analysis
    What are the current market conditions, what is the expected or best cost, etc.
  • Logistics
    What is the best method of transportation and how do you time it to optimize costs and revenues, etc.?
  • Needs Identification
    What do you need, when, and are there alternatives, etc.?
  • Negotiation
    What do you offer? What’s your minimal viable alternative? etc.
  • Project Management
    How do you balance your resources (time, money, talent) to achieve the goal? etc.
  • Resource Management
    What’s the best use of your limited resources? When do you buy and sell? etc.
  • Supplier Identification
    Which suppliers want to supply you? Which suppliers are acceptable to you? etc.
  • Trend Identification / Projection
    Are demands going to increase, decrease, or stay the course? etc.

These skills are not easy to come by and not easy to advance. For example:

  • Analysis
    requires mathematical skills and training
  • Logistics
    requires cost analysis and network modelling skills and training
  • Needs Identification
    requires the ability to elicit details from both analyses and stakeholders
  • Negotiation
    requires training and people skills
  • Project Management
    requires knowledge and training
  • Resource Management
    requires strong analysis skills and an understanding of the inherent value and limitations of each resource
  • Supplier Identification
    requires the ability to assess a supplier across multiple dimensions and know what those dimensions should be
  • Trend Identification
    requires analysis, statistical training, and an instinct for the right questions

Now do you understand why even if you could get approval for the staff you need, finding the right individuals might be hard?