ERP systems have been historically good at processing and recording transactions, but mining data for spend visibility was not one of them. Spend Analysis started in the early 1990’s at progressive companies like GE and at consulting firms like McKinsey. The idea was to mine existing spend data to identify areas where sourcing effort would be most profitable.
The idea in theory in the early days was cutting edge; however the methods to mine the data in an ERP system came with numerous problems including:
• ERP data is usually incomplete
• Contained duplicate vendors
• Poor commodity information
• Data is unchanging
Let’s dig deeper into these problems to better understand them.
ERP Data is Generally Incomplete: ERP systems record transactions which they are designed to do. However, they only record transactions that are made in that system and do not account for other systems that process transactions including P-cards. ERP’s also do not contain important SA information about supplier diversity, risk and scorecard metrics.
ERP Systems Contain Duplicate Vendors: An ERP system records the data that is entered in the transaction. It doesn’t consolidate their transactions into one supplier entity. For example, you could have 16 different transactions, with 16 different versions of Federal Express. Your transactions are just with FedEx, but it looks like you have 16 different suppliers. So you really have no idea how much you are spending with FedEx as a whole unless the transactions are entered identically by different people.
ERP Systems Don’t Contain Good Commodity Information: A good ERP system provides the ability to assign category codes to transactions, but the practitioner who is entering in the transactions usually is not well versed in the coding structure. In many, cases people don’t take the time to find the correct code, because they don’t understand the importance of it.
ERP Data is Unchanging: ERP systems are financial accounting systems by nature and because of that are designed to be rigid and make changing information about vendors or category codes very difficult. It can take weeks or months to modify the information.
All of these issues cause a very cloudy view of Spend Analysis. The problem multiplies itself with large global corporations, or with mergers and acquisitions, where you have numerous disparate ERP systems that don’t talk to each other. With incomplete, bad data, enormous savings opportunities are missed. This is where the data ends and the role of spend analysis begins. Stay tuned for Part 2: What is the value of Spend Analysis?
For more information about this topic and Spend Analysis click here for our White Paper.
One of the big cost and “choke” points in Spend Analysis has been the difficulty in collecting the many different sources of Spend related data. Spend data typically resides in disparate systems, including ERP, AP, PO, Pcard, Suppliers, Supplier enrichment, Expenses, Invoices, Freight Bills, financial systems, sales systems, and more. Spend data can also be spread across many different company locations and systems, as well as available only in foreign languages, thereby making “all” Spend data very difficult to collect. Comprehensive Spend data is needed to achieve more in-depth Spend visibility and to uncover larger cost savings for the company. Typically in the past, vendors required companies to format the data, so it could be put into a fixed database, so it could be rendered to fixed reporting and analytics capabilities. Now that has all changed.
No, data cannot be collected in 10-15 seconds, aka Star Trek “Transporter” capabilities. But today’s data collection capabilities are not far off either. With newer data management applications having underlying dynamic database “data driven” technologies applied, company data can now be collected, audited, and cleansed easily, and in a short amount of time (in hours, vs. days and weeks). All that is needed is a header row defining the file’s data fields, a related template defined, and data validation and integration points applied. This is now done within the vendor data management system, so no IT burden is placed on the organization, except to forward month-end or year-end Spend related files as appropriate, which is an easy thing to do. No more data extraction templates forcing IT people to do field mapping and hard-code their own fields to fields that are predetermined. No data formatting to prescribed translation maps finding places for extraneous or custom data within a fixed database. Simply forward a Spend-related file to a vendor FTP site, and they take it from there.
This new data collection capability may be hard to initially comprehend, but now you can enjoy the ability to easily collect more expansive Spend related data, and drive new analysis and management capabilities. The more complex your organizational disparate data is, the more that “data driven” capabilities apply.
The available selection choices are not truly relevant to new “data driven” Spend Analysis applications. Dynamic database technology saves IT departments’ hours, if not days and weeks of work, and shortens the time to deployment or refresh. Essentially, translation maps are obsolete and a rigid element of the past.
2010 should bring a flurry of new acquisitions with many established companies looking to expand product lines and increase growth within the organization.
Of these companies looking to expand through acquisition, raising capital expense to fund the newly acquired business unit will be a challenging experience in ramping-up operations with manufacturing and warehousing distribution.
Many companies will be looking to outside warehousing and distribution ( 3PL’s ) assistance in order to compensate the need to either add-on to a existing building or to reorganize a current floor plan.
It makes perfect sense when acquiring a new business unit to have the flexibility of outside warehousing and distribution. With all the challenges the current organization has with product line simplification, product integrity, customer retention and merging of operations and customer service the 3PL can add much value to the company but lending it’s expertise in distribution challenges.
Having the flexibility and an open working communication with the outside warehouse and distribution facility allows valuable time to evaluate and streamline the newly acquired business unit or product line.
The organization can now grow and nurture the new product line or reduce the number of SKU and not have it interfere with the current core business.
In the world of Spend Data Management and Spend Analytics, not much new technology has come forth over the past 5 years, until now. We have been stuck with ETL’s requiring structured data templates, fixed databases, reporting cubes, and manual data classification to name a few. Each of these technologies had less-than-desired automation and difficulties, or “choke” points, along the Spend Analysis process of collecting data, integrating it, cleansing it, classifying it, and analyzing/reporting on it for company Spend insights and cost savings opportunities. The new technology is known as “Dynamic Database” technology, and it is an advanced data processing capability perfect for Spend Analysis, Spend Management, and Category Management.
Dynamic database technology can quickly become a very technical discussion, and although it is revolutionary, it is not widely known beyond database guru’s, such as Oracle engineers. It is not like you start out with an existing car with no motor and customize the engine (an existing technology and tailor it). Everything about a dynamic database is setup for a specific purpose… you guessed it… “dynamically”. Applying it to the world of Spend Analysis, with real world examples, can help explain how it has opened up new capabilities in Spend Analysis not previously available with older technologies:
Examples and expanded capabilities of dynamic database technology across the Spend Analysis process:
Data Collection. Each companies specific data and business of sourcing, and we mean everything, can be accommodated, including global data in foreign languages. The data capture process is dynamic, meaning any data can be collected in any format easily. No formatted extracts are required.
Data Validation, Integration, and Cleansing. How data is validated…is dynamic, as data can now be integrated in ways it has never been integrated before, and cleansed more thoroughly across the additional relationships that are created.
Data Classification. How that data is classified…is dynamic, so multiple taxonomies can be supported independently AND related to each other. The rules that operate on the data are dynamic, and can be applied leveraging years of project and industry experience, as well as specific company business anomalies.
Analysis and Reporting. How data is reported…is dynamic, as all data is in memory and many core views and metrics across the customer data can now be rendered. Virtually any data collected can be reported. Strategic Sourcing and Category Management programs can be mirrored and monitored over time (with easy data refresh). Any change in business requirements and analysis needs can be accommodated by quickly collecting pertinent data and making simple reporting adjustments.
Application Interface. What really advances dynamic database technology is controlling all data and the related QA processes through a Spend Analysis application interface, making it flexible and easy to use.
Dynamic database technology, combined with a robust application interface for data collection, cleansing, classification, and reporting, is very unique and very powerful for Spend Analysis. It is a huge differentiation and advancement from previous methods and technologies. It truly raises the bar regarding what companies can now do to enhance Spend visibility, find new cost savings, and manage those savings.
Effectiveness, is key to competing in today’s business environment. Logistics is a process, a supply pipeline which connects you with your vendor/supplier and your customer.
Whether you compete domestically or globally competitors, vendors, suppliers and customers are worldwide.
The significant cost of logistic/distribution effects the entire supply chain. Logistics importance integrates and develops long-lasting alliance is between the vendors/suppliers and customers. Logistics contributes to a competitive advantage, viewed as a comprehensive process objective, making your product more competitive in the global marketplace.
Ask yourself how does your business unit measure up? Is your logistic/distribution network competitive? Does your current logistics/distribution network meet the requirements of your customer? Most importantly is it currently effective?
To summarize, a formal logistic program will create a competitive advantage for your business unit.
Service and cost benefits can distinguish you from your competitors.
A formal logistic network program will enhance your status as a supplier domestically and more importantly in the global network.
To approve Spend Analysis projects, project Sponsors often need to justify to their management why they need to utilize Spend Analysis providers to do the project, as opposed to internal IT resources. Some companies may not have this problem in that they don’t have IT resources available, so it is obvious they need to use outside help. But sometimes there may be conflicts internally. The simple answer is that internal IT resources usually do not have the focused experience and knowledge regarding the unique data cleansing and classification needed for Spend Analysis.
Internal IT resources typically have…
Familiarity with the corporate data sets and applications
Familiarity with the Corporate IT environment
Familiarity with a Corporate Reporting tool
Internal IT resources likely do not have (and Spend analysis providers have in spades)…
Related to (1) above…. IT resources can easily provide data files, but Vendors are more experienced to integrate and reconcile organizational data to specific Spend fields needed to properly drive meaningful Spend Analysis. Significant relationships exist between Spend data, and vendors know what to look for. They also have structured tools to process the data effectively.
Related to (3) above – IT resources can help with getting cleansed and classified data back into the company reporting environment, if a company reporting tool exists. Companies can also utilize vendor “Smart” Reporting, which is tailored for detailed Spend visibility and opportunity assessment.
Experience with cleansing data – for example, we have over 50,000 cleansing rules built over 12 years across over 200 projects and customers in many industries, already defined.
Experience with Supplier Grouping.
Experience optimizing Supplier data enrichment from vendors such as CVM Solutions or D&B.
Experience with data classification, handling numerous taxonomies for analysis, and grouping Spend data into meaningful sourcing categories. For example, we have a master library of over 100,000 master rules for items and categories we have seen across all those projects mentioned above.
Experience with structured data “refresh” and handling the nuances of combining, re-cleansing, re-grouping, and reclassifying data with rigor to all the taxonomies in use.
Experience in foreign languages and associated data processing and translation.
Experience in mining and reporting in-depth level s of “savings opportunity assessment and identification” versus basic pivot tables and cubes.
Internal IT resources usually do not have authority across divisions and countries to get data, so a vendor can help to make the integration and change happen.
Spend Analysis vendors provide focused tools and resources to implement advanced Spend Analysis within your organization, and can be utilized effectively in place of internal IT resource. And the cost is usually less than 1 or 2 full time equivalent headcount, which is a bargain as you discover savings opportunities.
Telecom is normally one of the largest spend categories that is over looked within large multi-national corporations. Most CIO’s don’t have the knowledge or background to understand the spend they have in Telecom. This lack of understanding leads to very ineffective Telecom sourcing projects.
According to research conducted by Forester Consulting, “80% of all telecoms sourcing projects are not as efficient as they should be, and large organizations globally are feeling the effect to the tune of £12bn annually.”
This is a large amount of savings missed because of poor visibility and understanding when running these projects. This is a complex category in which IASTA has had enormous success in continually producing savings. We have continually been able to provide at least an 8% savings to clients in this one category alone. This small percentage in savings equates to a large dollar savings when looking at the total spend in Telecom.
As the article goes on to state, “this issue is one of getting in the right people who understand the technology and the objectives of a telecoms sourcing strategy.”
Take a close look at your internal knowledge base of Telecom and see if this is an area that is not producing optimal results when it should.
Numerous larger organizations, such as international or holding companies with disparate global operations, often have difficulty getting an organizational Spend Analysis project launched, primarily due to the independent operations within each company in the portfolio. A typical, comprehensive Spend Analysis project would address all Spend. This is typically all AP, PO, P-Card, and Expense data across all sites and systems. These companies would argue that opportunities to better leverage spend do exist, but the challenge of coordinating efforts across disparate operating units has historically slowed adoption within these firms. For these types of situations, a phased approach to Spend Analysis is a solid deployment method that enables the company to start identifying and executing on savings opportunities while gradually incorporating other business units. Outlined below are the most common examples:
Alternative Approach 1 – Accounts Payable Focus: Extracting data out of the Accounts Payable systems is generally a straight-forward process. While A/P alone does not provide the same level of insight as does the Purchase Order/Expenses/P-Card data, it often reveals many savings opportunities that can be addressed immediately. This approach can be further simplified by applying a reverse Pareto principle – only extracting the top 80% of the A/P spends. As sourcing opportunities are identified at this high level, they can then be further broken down during the sourcing initiative and additional data collected as appropriate.
Alternative Approach 2 – Geography/Operating Unit Focus: Some organizations decide to focus on an area they can control, such as a particular geography or business unit, and collect more detailed data for that area. In this manner there are fewer people involved and they can get very detailed visibility into data and sourcing opportunities for the area in scope. The data can then be extrapolated to the entire company as targeted sourcing efforts are conducted.
Alternative Approach 3 – Category Focus: Some organizations identify a top 10 list of Spend categories that they know can produce cost savings, and then collect as much data as they can from those sites having a good amount of these Spend categories. (Areas such as Ocean Freight, Print, Office Supplies, Telecom, Temp Labor, etc.) The data is then quickly extracted from the overall data set and analyzed for the specific perceived opportunities. Only the Spend for those initiatives is focused in the data classification process.
Alternative Approach 4 – A Combination of the Above: Invariably, a Spend Analysis project comes down to people and executive sponsorship. It has been proven over and over again that savings exist well beyond the cost of any Spend Analysis project (10X to 50X ROI). But typically it is hard to get sponsorship organization wide, as this usually requires the involvement of the CFO and even the CEO. The CPO, or Director of Strategic Sourcing, has a span of control (and budget) that they can use to get some form of Spend Analysis project started. As even small Spend Analysis projects can produce large savings, getting something started and generating a quick ROI can be leveraged to look further and deeper across the organization. Those initial savings can be invested forward to get more approval to conduct more projects with larger scope. We find this is very common to exercise the largest span of control a person may have who believes in the value of Spend Analysis done right, and they go after the corresponding savings that can be achieved.
Have you ever considered taking the air or reconfiguring your current packaging?
Many companies do not take the time to analyze their current packaging of finished product once the product has been prepared for the end-user.
Many times I have walked through distribution warehouse centers and simply picked up a master carton of blister carded product and gave it a real good shake it’s amazing how much wasted space is in that carton.
Think about it, air probably makes up 10 to 15% of the carton contents along with the blister carded product and serves absolutely no purpose other than taking up excess space.
Multiply that carton by how many other cartons are stored on that skid with the 10 to 15% of excess air contained in the package and overall you may have 75% product 25% air stacked in a single bin location.
Excess air in packaging results in higher warehouse storage costs, increased classification of product for carrier tender equals higher transportation costs, plus out of spec carton configurations results in higher component costs.
In the grocery industry many consumers will start seeing new package configurations for many of their favorite cereals and snacks, manufacturers of these products are developing ways of reducing size and packaging costs by reconfiguring packaging and ensuring product integrity.
It is important for manufacturing to periodically review and evaluate current packaging of their product, in order to determine if costs and distribution in transportation are being maximized and are not storing excess air in the packaging.
More companies are looking at centralized distribution and servicing their customer base in a timely manner in order to control costs, control inventory overhead and to improve overall customer service.
Centralized distribution sometimes has its own challenges and issues based on schedules, inventory and transportation network.
Other factors that should be considered is the size of the of the distribution center, the layout of the facility and capabilities of handling many more multiple shipments on a daily basis can result in many more LTL carriers.
Zone distribution to major market zones can eliminate much of the congestion and the handling of freight multiple times elevating issues with shortages, damages, and non-timely deliveries.
It is important to identify major market demographics pertaining to customer base, product distribution, field sales force and capabilities of end users and master distributors.
A major candle manufacturer based in the United States was faced with major issues such as damages, lost shipments, inventory shortages and untimely deliveries.
By developing major market zones utilizing 80/20, the manufacturer was able to overcome many of the above challenges and issues by driving carrier tender to specified market zones based on schedules ultimately utilizing local end-user delivery suppliers.
Many of our customers ask us to handle their Supplier data enrichment data. This is a natural fit to add and integrate this informative data to all the supplier and Spend data that is collected. Supplier enrichment data packets build additional analytical and Spend management capabilities into the overall Spend Intelligence warehouse. However, many organizations do not add this important information such as DUNS/SIC/NAICS/Parent Child, Diversity, and Risk related Supplier information, as it can get quite expensive in a hurry, if the overall process is not managed and optimized to the company’s overall needs.
Adding this data into your Spend Intelligence warehouse should simply be another source file. We have relationships with all the major companies that provide Supplier Enrichment data, and having done this many times, we have optimized the overall process and related expense to get this information integrated with your Supplier and Spend information.
Optimizing the Supplier Enrichment process is as follows:
Create a Clean Vendor Master – through the Spend data collection process, suppliers are collected from all sites, cleansed, grouped, classified, and rationalized to a consolidated vendor master. Now the company can break down their suppliers relative to Spend and priorities as to which ones should potentially be enriched.
Mix and Match Supplier Enrichment Data Packets – enrichment data for SIC/NAICS or Parent Child relationships are usually in different data packets than data packets for diversity and risk. Each data packet has different costs, with risk usually being most expensive. You can analyze your supplier base to determine which suppliers should get what level of data packet, such as only preferred suppliers, or suppliers with large Spend dollars, have risk-related enrichment.
Process and Integrate Suppliers to/from the Provider – the handshake of providing the actual supplier file to the supplier enrichment provider, getting it back, and integrating it into your Spend warehouse, should be handled easily by your Spend Analysis provider.
Create More Advanced Analytics, Reporting, and Spend Management programs – once the data is received back from the supplier enrichment provider, it must be integrated with all the related Spend data for that supplier. In addition, the new data can now be added to the overall analytical capability the organization needs to track diversity, compliance, conduct deeper analysis, and better manage overall sourcing programs.
All the above should be done easily (and at low cost) by your Spend Analysis provider, thereby creating significant value to handle this important and more advanced management capability for your organization.
I have noticed an interesting trend that has played out over time, and seems to be increasing in popularity. And that is, many companies are no longer looking to classify their data to UNSPSC codes. What I have noticed over literally more than a 100 Spend Analysis projects over the past 10 years, is that companies do not “source” by UNSPSC codes. And UNSPSC codes do not naturally roll-up to sourcing categories as the company would like to see.
For example, If you were to go and source IT spend within UNSPSC, then you would have to look in segments 43 for all the equipment, 8111 for Computer Services, 80101507 for IT Consulting, and 831124 for Internet service providers. That is 4 different segments across the range of Segment, Family, Class, Commodity codes. If you were a category manager looking into UNSPSC you may find one or two of the categories fairly quickly but to find it all may take time, and it is not totally trusted that you “have it all”. Another common example is software…the actual software codes are in one area (4323 and below), and the support and maintenance fees are in a completely different segment (811122). When you source software you need to look at both components…because both are negotiable as a combined Spend.
The above are good examples of why a category roll-up feature is critical. And there are many more examples across many UNSPSC codes – codes that need to be tied together or “rolled-up” into company sourcing categories. I find that all organizations want the trusted category roll-up information for larger sourcing leverage, and to match their sourcing needs. As such, UNSPSC has become a “middle man” – a way to move the ball up and down the field and get some insights into Spend data. UNSPSC seems to apply better on the direct side of a companies Spend, but not so much on the indirect side – a big area for savings opportunities, and an area where details are more difficult for UNSPSC classifications.
What companies are doing in many cases now, and with new capabilities provided by Spend Classification tools, is classifying raw data straight to sourcing categories. That is the end-goal, after all, correct? And as that increases in popularity, the old standards like UNSPSC, or eCl@ss, etc will become less and less important. They all become a means to analyze data, but are not necessary to create sourcing categories and support company sourcing programs.
Of course with the new Spend Analysis tools you can have both, and more, if you desire. Both UNSPSC classification and company Sourcing Categories – all tied together. And you can add other taxonomies as needed. Multiple taxonomies can provide multiple dimensions for advanced Spend Analysis, and that is good. The more classification taxonomies, the more you can break down and analyze data. But increasingly so, the focus is on classifying to Sourcing categories, and longer term management around those categories. That seems to be leaving the “middle man” out of the picture.
In Part 1 of this post, I discussed some of the shortcomings to rely on a Proof of Concept as the main decision point to select a particular suppliers Spend Visibility solution. If you decide a POC is required as part of your selection process, below are some suggestions as to how to most effectively conduct the POC as part of your overall selection process.
Some “Pros” of Conducting a Spend Data Classification Proof of Concept
Allows sourcing people to throw data over the wall and see who responds.
Enables companies to see their data reflected in vendor Spend tools, and companies can see how they would interact with their own data.
Provides an idea of the vendor classification capabilities to a standard classification schema, like UNSPSC.
A Better Process
Don’t do a POC too early in the selection process, and as a key selection event focus, or you may miss larger approaches to Spend Data Classification that better match your company sourcing programs. Not just UNSPSC classification, but also sourcing category classification that will support your organizations sourcing programs.
When you provide company data, focus on areas that may provide new opportunity, which helps everyone focus on the best job possible (savings opportunities are good).
Do a POC to see your data in the vendor tool and prove it out, but define a realistic (but meaningful) sized data set.
Focus on the vendor classifying to your Sourcing category structure, not just UNSPSC or other.
Allow for a hands-on workshop to review the classification process and see full blown vendor capabilities for the long haul. It is through these workshops that enable you to really see what goes on “behind the scenes” and separate out fact from fiction.
In today’s world of vendor selection for company Spend Analysis needs, the process “du jour” is to have the vendor conduct a free “Proof of Concept” (POC), Pilot, or classification test. Increasingly, this selection process is based on older standards for Spend data classification, and has become an incomplete test of a long term, successful Spend Analysis and larger “Spend Visibility solution” for your company’s Sourcing programs. Classifying data in some manner, which is an important step in ultimately finding cost savings, may be testing the size of a vendor’s pre-sales group, and may not be at all reflective of many other very important and critical capabilities that will make your company find and manage larger cost savings over time.
Some “Cons” and Missing Links
Usually a POC is done in a short time-frame; classifications are to UNSPSC, with minimal company sourcing categories and programs information.
How easy is it for a vendor to provide a good end-result, but hide difficulties and secrets, by having numerous resources put on the project (pre-sales people)? How was the classification really accomplished? The “how” will matter much more over time for your company’s on-going sourcing need.
Conducting a POC classification to UNSPSC does not test the ability to how a vendor can “roll-up” to the company’s sourcing categories, and how the classification can support the company’s strategic sourcing programs. Data classification must ultimately end up in rolled-up sourcing categories, and then be managed from there (category management – another post).
AI isn’t BI. Artificial intelligence works to a standard, like UNSPSC. But UNSPSC is being used less and less, as it is difficult to source from UNSPSC codes. If UNSPSC is not used to source, why “auto class” to it? A company needs real business intelligence specific to their sourcing programs, which of course is different from company to company, and is not conducive to AI.
Auto classification isn’t cutting it – How can “auto classification” be intelligent to a company’s sourcing categories, if every company’s taxonomy is different at a detail level?
Where in the process are you able to view the feedback and control mechanisms to refine data accuracy? You don’t want to discover problems in the months ahead, when you do more detailed sourcing projects.
You don’t really see the speed – to accomplish data classification specific to your business needs quickly and easily.
You don’t see transparency of your data – where it is, where it will be, and what happens to it.
How does this position your company for a real implementation (pre-sales people won’t be implementing)?
How does this show structure and repeatability for future refreshes of data?
Usually a POC does not incorporate new company data collection capabilities for advanced Spend Analytics, which will happen over time as the company matures.
Usually a POC does not focus on reporting, opportunity assessment, Spend measurements, and compliance capabilities.
In Part 2 I will discuss the benefits of doing a “Proof of Concept” and how to do it in the most optimal way.
What’s a buying/leveraging group?
A buying group is a collection of buyers that aggregate their demand into a single ‘account’ and negotiate with a commercial carrier/s for better prices and/or improved services and more importantly a “Known name” in the industry. The group of buyers should be organized around an industry sector or geographic region.
How do buying/leveraging groups work?
A group is usually formed when an individual or business decides use bulk buying tactics for transportation services. Once a sufficient group of customers is formed, the guaranteed customer base is used to negotiate volume discounts with service providers and carriers.
What are the advantages?
Buying groups are low risk and require little or no investment and the groups don’t have to be physically co-located just share the same “common goal.”
What are the drawbacks?
Buying groups depend on a guaranteed level of spend and are therefore at risk of being undermined by carriers offering the larger companies in the group separate deals (known as ‘cherry picking’) the group must also be accountable and be geared towards the 80.
Summarize:
The buying group or leveraging group is making a commitment to each other business unit to share information and a “guaranteed” piece of the business. “Commitment” is the largest most important piece of the organization and must be maintained and monitored on a regular basis and each business unit must have a say in each and every move.
Buying groups can grow expeditiously to encompass other units….. all geared to the “common goal.”
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