* the doctor does not endorse the use of Prozac or any other anti-depressant, whether or not they are in the selective serotonin reuptake inhibitor class, unless prescribed by a certified medical professional who has taken you under his or her care.
Monthly Archives: July 2014
Could You Be Doing It Right? Part III: Big Data
In last Friday’s post, we asked if you were doing it wrong. In particular, we mentioned category management, supply chain risk monitoring, and big data, and asked if you were doing them wrong. We noted that even though a number of companies have jumped on these runaway bandwagons, most have yet to grasp the reigns and take control of the wagon and get it on the right track.
Why is that?
Fundamentally, it’s the same reason that there are no world class Procurement Organizations in Asia Pacific — the classic Triple-T problem.
- Talent
the organizations don’t have the right talent to properly manage the initiative - Technology
the organizations don’t have the right platforms to capture the right data and support the right processes - Transition Management
the organizations don’t have the right processes in place to handle the necessary organizational shift to properly manage the initiative
Once the talent, technology, and transition management is in place, the organization has what it needs to fully embrace the initiative and take it to the next level. And do it right.
Where should your Supply Management Organization start? By identifying the core capabilities that are required in each “T” category and finding the right talent, technology, and transitions management for the initiative, the organization will be well on its way.
In the rest of this post, we’re going to talk about the requirements for an organization to get on the right category management track.
Talent for Big Data
Good big data scientists need the following hard and soft skills:
- Algorithms
there’s no magic algorithm where big data is concerned as every problem is unique and requires a unique (variant of an) algorithm - Domain Knowledge
the scientist needs to know when she can be confident in the data and when she can’t; if there is not enough data, or the data is too random or skewed from expected patterns, then the scientist needs to know to trust judgement over data - Technical Skills
the scientist needs to use sophisticated tools to perform her analysis - Logic
the data, and algorithms, are very precise and the data scientist needs to be as well - Teaching
since the majority of organizational employees will not understand what the big data scientist does, she will have to be able to explain what is needed data-wise, what the meaning of the results are, and how confident the organization can be in the results in simple terms - Perseverance
since big data isn’t as simple as just dumping a bunch of data into an algorithm and accepting the result; the first, second, and tenth try won’t always generate a useful result — sometimes the data scientist, like an archaeologist, has to dig, dig, dig
Technology for Big Data
Appropriate technology platforms for big data will have at least the following features:
- Big Data Stack
You need an infrastructure that is scalable, replicable, and fault-tolerant. - Domain Specific Algorithms
That can run on the stack and analyze the right data in the right way to generate some useable facts. - Powerful Reporting Engine
That can not only generate reports useful to the scientist but to others in the organization. - Powerful ETL Middleware
As you will need to extract, transform, and load data from a wide variety of sources.
Transition to Big Data
In order to transition to an organization that properly uses big data, the organization needs to hire someone with good change management skills and give that person the tools and C-suite support he or she needs to get it done. That person also needs to be a natural born leader and someone who can work with teams to get it done.
This isn’t a complete (laundry) list of what is required for big data, but it’s a good starting point. Get the right talent, technology, and transition management in place, and your organization will be well on its way to big data* success.
* Especially if you hire a good big data scientist who recognizes that sometimes the data doesn’t have to be all that big to derive a useful fact!
Could You Be Doing It Right? Part II: Risk Monitoring
In last Friday’s post, we asked if you were doing it wrong. In particular, we mentioned category management, supply chain risk monitoring, and big data, and asked if you were doing them wrong. We noted that even though a number of companies have jumped on these runaway bandwagons, most have yet to grasp the reigns and take control of the wagon and get it on the right track.
Why is that?
Fundamentally, it’s the same reason that there are no world class Procurement Organizations in Asia Pacific — the classic Triple-T problem.
- Talent
the organizations don’t have the right talent to properly manage the initiative - Technology
the organizations don’t have the right platforms to capture the right data and support the right processes - Transition Management
the organizations don’t have the right processes in place to handle the necessary organizational shift to properly manage the initiative
Once the talent, technology, and transition management is in place, the organization has what it needs to fully embrace the initiative and take it to the next level. And do it right.
Where should your Supply Management Organization start? By identifying the core capabilities that are required in each “T” category and finding the right talent, technology, and transition management for the initiative, the organization will be well on its way.
In the rest of this post, we’re going to talk about the requirements for an organization to get on the right supply chain risk monitoring track.
Talent for Supply Chain Risk Monitoring
Good risk managers need the following hard and soft skills:
- Analysis
On what services, products, components, and raw materials is the organization (most) dependent and which of these are sole-sourced and/or in scarce supply. - Mapping and Modelling
What does the multi-tier supply chain look like and how can it be represented in software? - Mitigation Planning
If a certain raw material, component, product, or service becomes temporarily, or even permanently, unavailable, what other options can be put into action? - Insight
The greatest risk is always where you least expect it. You will need someone with great insight to not only determine what types of risk you may face, but how your organization can most effectively monitor for them. - Sportsmanship
You will need a great team player to bring it all together. - Crisis Management
When the proverbial sh!t hits the fan, and the organization goes into panic, you need a strong, level-headed crisis manager to get them back on track quickly, and without loss.
Technology for Supply Chain Risk Monitoring
Appropriate technology platforms for risk monitoring will have at least the following features:
- Supply Chain Mapping
the platform should map your supply chain multiple tiers down to the source raw materials for any raw materials you are dependent on - Event Monitoring
the platform should identify any natural or man-made disasters that can disrupt your supply chain - Mitigation Planning
the platform should allow the risk manager to put together plans of action should any required part or raw material become unavailable - Response Management
the platform should allow the incident management team to manage the response to a disaster when it occurs - Mobile Interface
as people need to be able to access the platform from anywhere, wherever they are, as the disaster could take out your primary offices
Transition to Supply Chain Risk Monitoring
In order to transition to a proper supply chain risk monitoring framework, the organization needs to hire someone with good change management skills and give that person the tools and C-suite support he or she needs to get it done. That person also needs to be a natural born leader and someone who can work with teams to get it done.
This isn’t a complete (laundry) list of what is required for proper supply chain risk monitoring, but it’s a good starting point. Get the right talent, technology, and transition management in place, and your organization will be well on its way to risk management success.
Could You Be Doing It Right? Part I: Category Management
In last Friday’s post, we asked if you were doing it wrong. In particular, we mentioned category management, supply chain risk monitoring, and big data, and asked if you were doing these three thing wrong. We noted that even though a number of companies have jumped on these runaway bandwagons, most have yet to grasp the reigns and take control of the wagon and get it on the right track.
Why is that?
Fundamentally, it’s the same reason that there are no world class Procurement Organizations in Asia Pacific — the classic Triple-T problem.
- Talent
the organizations don’t have the right talent to properly manage the initiative - Technology
the organizations don’t have the right platforms to capture the right data and support the right processes - Transition Management
the organizations don’t have the right processes in place to handle the necessary organizational shift to properly manage the initiative
Once the talent, technology, and transition management is in place, the organization has what it needs to fully embrace the initiative and take it to the next level. And do it right.
Where should your Supply Management Organization start? By identifying the core capabilities that are required in each “T” category and finding the right talent, technology, and transition management plan to support the initiative, the organization will be well on its way.
In the rest of this post, we’re going to talk about the requirements for an organization to get on the right category management track.
Talent for Category Management
Good category managers need at least the following hard and soft skills:
- Analysis
to determine the volume and spend in the category - Modelling
to determine the major cost components, and cost drivers, of the major products or services in the category - Commodity Market Expertise
in the major raw materials and commodities used in the production of the major products in the category - Stakeholder Management
as savings and performance improvement will usually come from consolidating related items with a smaller set of suppliers, which is going to ruffle some feathers when some departments lose their coveted suppliers and supply relationships. - Negotiation
since not only will the individual need to consolidate a set of commodity purchases with a single supplier, but the individual will also need to cut a good deal and maybe even convince the supplier to take some business it normally wouldn’t want - Change Management
since good category management typically requires changing the way the organization conducts business today
Technology for Category Management
Appropriate technology platforms for category management will have at least the following features:
- Spend Analytics
with extensive aggregation, cubing, and filtering capability
as the category manager needs to not only extract volume and spend, but identify related products and services based on components, raw-materials, and sub/related services - Should Cost Modelling
which allows the category manager to understand not only what the product should cost but the primary cost components and the appropriate inputs to an optimization model - (Real-Time) Market Data
which allows the category manager to track historical market trends and predict future prices to time the market if prices are volatile - Supplier Performance Management
which allows the category manager to track and manage supplier performance - RFX
to manage the data collection and track supplier bids and responses before and during negotiations
Transition to Category Management
In order to transition to proper category management, the organization needs to hire someone with good change management skills and give that person the tools he or she needs to get it done. That person also needs to be a natural born leader and someone who can work with teams to get it done.
This isn’t a complete (laundry) list of what is required for proper category management, but it’s a good starting point. Get the right talent, technology, and transition management in place, and your organization will be well on its way to category management success.
SIM? Is It Old News or a Shiny New Pair of Shoes? Part II
As per our last post, SIM (Supplier Information Management) is a mature and stable technology with a large number of suppliers not only providing the tools and best practices to manage supplier life-cycles, but to manage risk, compliance, receivables, and even spend repositories for spend management. It’s almost a commodity in the Supply Management Space, and an acquisition thereof is not likely to get baby that new pair of shoes anytime soon. Or is it?
As great as they are, most SIM products — stand alone best-of-breed or integrated suite offerings, have at least one weakness — and often two. In particular, the data model and the workflow. Just like early spend analysis solutions were often tied to one, rigid, UNSPSC data model, most current SIM solutions are also tied to one, rather rigid, data model. In addition, most of those solutions with some SLM (Supplier Lifecycle Management) also have rigid workflows.
This worked well when business processes were predictable and stable and corresponded to products with long life-spans. But the times they-have-a-changed. These days, product life-spans are measured in quarters, and not years, if we are lucky. Associated processes change to not only accommodate the new product demands but to adapt to new technologies and new business requirements. If the workflow can’t adapt, the capability, and overall usefulness, of the tool is limited.
A SIM product that could not only allow a user to define, and redefine, data models as necessary but define, and redefine, workflows as necessary would offer more value than current SIM platforms. And if that product could also maintain full audit trails, which not only track data changes but model and workflow changes, and insure that old records and workflows can still be seamlessly accessed when the data model or workflow changes, then that would be even better.
And if that SIM product went even further and allowed for dynamic organizational, supply base, and user-defined hierarchies, that would be icing on the cake. Supply Chains are not boring because they are not static. They are constantly changing. The supply chain can not only change from product to product, but batch to batch as a primary raw material or part supplier runs out of material, becomes unreachable due to a political or natural disaster, or simply gets greedy and forces the higher tier supplier to find a new source. A good SIM solution will allow the supply chain map to evolve in real-time as the supply chain evolves. Moreover, with acquisitions, mergers, and spin-offs being the normal modus operandi for many businesses, a SIM solution that can easily adapt the organizational data model is also required. Finally, for maximum productivity, a user needs to be able to maintain their own view of the supply chain, back and front, relevant to them. They need to maintain their view of the relevant multi-tier supply base and the relevant hierarchies in their organization that they have to report to and serve.
In other words, a SIM tool that allowed for a truly dynamic data model, workflow, and supply chain organization map could bring a new wave of value to a modern Supply Management organization and the individual with the foresight to acquire such a tool might just get baby a new set of shoes. But is there such a solution?
Stay tuned!