Project Planning Package – SAP SmartOps

How it Works

Fill out the form below for your project planning estimate. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust.

Details

  • Vendor Name: SAP (See for Vendor Rating)
  • Software Category: Production Planning and Detailed Scheduling
  • Company Headquarters: Dietmar-Hopp-Allee 16, 69190 Walldorf, Germany
  • Site: http://www.sap.com
  • Contact number: 49.6227.747474
  • Delivery Mechanism: On Premises

Finished With Your Analysis?

Once complete, go to this link to see other analytical products for SAP SmartOps.

References

Risk Book

Software RiskRethinking Enterprise Software Risk: Controlling the Main Risk Factors on IT Projects

Better Managing Software Risk

The software implementation is risky business and success is not a certainty. But you can reduce risk with the strategies in this book. Undertaking software selection and implementation without approximating the project’s risk is a poor way to make decisions about either projects or software. But that’s the way many companies do business, even though 50 percent of IT implementations are deemed failures.

Finding What Works and What Doesn’t

In this book, you will review the strategies commonly used by most companies for mitigating software project risk–and learn why these plans don’t work–and then acquire practical and realistic strategies that will help you to maximize success on your software implementation.

Chapters

Chapter 1: Introduction
Chapter 2: Enterprise Software Risk Management
Chapter 3: The Basics of Enterprise Software Risk Management
Chapter 4: Understanding the Enterprise Software Market
Chapter 5: Software Sell-ability versus Implementability
Chapter 6: Selecting the Right IT Consultant
Chapter 7: How to Use the Reports of Analysts Like Gartner
Chapter 8: How to Interpret Vendor-Provided Information to Reduce Project Risk
Chapter 9: Evaluating Implementation Preparedness
Chapter 10: Using TCO for Decision Making
Chapter 11: The Software Decisions’ Risk Component Model

Enterprise Software TCO Calculator – SAP SmartOps

How it Works

Fill out the form below for a your customized TCO calculation, as well as each of the supporting cost components that make up the TCO. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust.

Details

  • Vendor Name: SAP (See for Vendor Rating)
  • Software Category: Production Planning and Detailed Scheduling
  • Company Headquarters: Dietmar-Hopp-Allee 16, 69190 Walldorf, Germany
  • Site: http://www.sap.com
  • Contact number: 49.6227.747474
  • Delivery Mechanism: On Premises

Finished With Your Analysis?

Once complete, goto this link to see other analytical products for SAP SmartOps.

MUFI Rating & Risk – SAP SmartOps

MUFI Rating & Risk – SAP SmartOps

MUFI: Maintainability, Usability, Functionality, Implement ability

Vendor: SAP (Select For Vendor Profile)

Introduction

SmartOps, before its acquisition by SAP in 2013 was one of the significant inventory optimization vendors. For some years SmartOps was involved in partnership with SAP, where SAP was primarily a reseller of SmartOps. This was one of the primary ways that SmartOps became the best-known inventory optimization and multi echelon-planning (MEIO) vendor. It was not, as SmartOps has repeatedly proposed (or believes themselves) because they had the best technology.

Application Detail

SmartOps Demand Analytics

SNP is marketed as a leading solution, but it does not have the most advanced method in supply planning, which is inventory optimization and multi echelon planning (MEIO). There are some reasons why MEIO is a far better method than cost optimization for supply planning. However, one of the most important is that service levels are far easier for companies to set than determining their costs. 

SmartOps was always more of marketing phenomena than an innovation leader; therefore its acquisition by SAP is a very logical move for the company. At SAP marketing is dominant, and technology is a distant second. In fact, SAP has been controlling SmartOps marketing messages essentially since they initiated their partnership — years before the acquisition.

SmartOps was the leading proponent of trying to simplify its marketing message to minimize what MEIO would do. In fact, MEIO should be used to replace the supply planning method and system. However, if SmartOps has taken this approach, it would have put them into conflict with companies like SAP. Therefore, they developed marketing message which allowed MEIO to be viewed as adjunct or assistive technology to either the ERP system or to the already installed supply planning system. In this case, SmartOps, or the MEIO application calculates merely master data parameters – the most common being the target stock level and even more commonly safety stock. These parameters are then entered into the ERP system or planning system, and then these systems go through their routine planning. The SmartOps approach greatly adjusted how MEIO was used and oversimplified the work that was required for companies to get their application to work correctly. We do not have a separate SmartOps vendor profile because the company no longer exists as an independent entity, however, if we did, we would point out that SmartOps was always more focused on what was marketable versus what was correct. It was their marketing that differentiated them from other MEIO making them the best selling MEIO application vendor, but unfortunately, this marketing has placed MEIO into a much smaller space than it should have been. This is one of many reasons that we consider the quality of information provided by SmartOps provided to customers to have historically been extremely poor. We have observed this not only through reading their marketing documentation but also in participating in software selection presentations.

As all acquiring software vendors do, SAP announced that the SmartOps acquisition was going to allow them to be more strategic than ever as the following quotation attests.

SAP has acquired SmartOps in a move the company says will allow it to develop real-time supply chain applications that take advantage of SAP’s HANA in-memory database.

However that is just for marketing purposes, in fact, the development of SmartOps will probably be only minimal from the time of the merger onward. This is a problem for buyers because SmartOps was a lagging application living off of its partnership with SAP when purchased, followed a flawed implementation approach (as described above), and has a low level of buyer satisfaction and a poor implementation track record.

For years SAP and SmartOps have been telling companies that these two solutions are integrated, but in fact, the integration of master data parameters is very simple. The applications are not integrated regarding transactions, so there is no point is paying much extra for this integration. Secondly, because SmartOps is just an adjunct to SNP or SAP ERP, much of the benefit of having an MEIO application is lost. This is not a solution architecture designed around business requirements or based upon leveraging MEIO functionality but is a marriage of convenience based on the fact that the dominant software vendor is offering a dated solution to their customers.

Both SNP and SmartOps are weak applications that score in the bottom of the supply planning software category. Combining them (in fact there only needs to be one external planning system) will not make them better, and would lead the highest TCOs of any supply planning solution on the market.

MUFI Scores

All scores out of a possible 10.

Vendor and Application Risk

SmartOps faces the similar issues of the problems that come with socializing inventory optimization. In reviewing post go-live projects with various buyers of inventory optimization software, it is quite common for many of the business users and the executives not to understand how inventory optimization works. SmartOps deliberately understates the complexity of inventory optimization to get the sale, which makes implementation difficult. There are also serious sustainability concerns when SmartOps is co-implemented with SAP SNP, as SNP already consumes so many resources just to keep operational.

Likelihood of Implementation Success

This accounts for both the application and vendor-specific risk. In our formula, the total implementation risk is application + vendor + buyer risk. The buyer specific risk could increase or decrease this overall likelihood and adjust the values that you see below.

Risk Definition

See this link for more on our categorizations of risk. We also offer a Buyer Specific Risk Estimation as a service for those that want a comprehensive analysis.

Finished With Your Analysis?

To go back to the Software Selection Package page for the Supply Planning software category. Or go to this link to see other analytical products for SAP SmartOps.

References

Brightwork MRP & S&OP Explorer for Tuning

Tuning ERP and External Planning Systems with Brightwork Explorer

MRP and supply planning systems require tuning in order to get the most out of them. Brightwork MRP & S&OP Explorer provides this tuning, which is free to use in the beginning until is sees “serious usage,” and is free for students and academics. See by clicking the image below:

Software Selection Book

SELECTION

Enterprise Software Selection: How to Pinpoint the Perfect Software Solution Using Multiple Sources of Information

What the Book Covers

Essential reading for success in your next software selection and implementation.

Software selection is the most important task in a software implementation project, as it is your best (if not only) opportunity to make sure that the right software—the software that matches the business requirements—is being implemented. Choosing the software that is the best fit clears the way for a successful implementation, yet software selection is often fraught with issues and many companies do not end up with the best software for their needs. However, the process can be greatly simplified by addressing the information sources that influence software selection. This book can be used for any enterprise software selection, including ERP software selection.

This book is a how-to guide for improving the software selection process and is formulated around the idea that—much like purchasing decisions for consumer products—the end user and those with the domain expertise must be included. In addition to providing hints for refining the software selection process, this book delves into the often-overlooked topic of how consulting and IT analyst firms influence the purchasing decision, and gives the reader an insider’s understanding of the enterprise software market.

This book is connected to several other SCM Focus Press books including Enterprise Software TCO and The Real Story Behind ERP.

By reading this book you will:

  • Learn how to apply a scientific approach to the software selection process.
  • Interpret vendor-supplied information to your best advantage. This is generally left out of books on software selection. However, consulting companies and IT analysts like Gartner have very specific biases. Gartner is paid directly by software vendors — a fact they make every attempt not to disclose while consulting companies only recommend software for vendors that give them the consulting business. Consulting companies all have an enormous financial bias that prevents them from offering honest advice — and this is part of their business model.
  • Understand what motivates a software vendor.
  • Learn how the institutional structure and biases of consulting firms affect the advice they give you, and understand how to properly interpret information from consulting companies.
  • Make vendor demos work to your benefit.
  • Know the right questions to ask on topics such as integration with existing software, cloud versus on-premise vendors, and client references.
  • Differentiate what is important to know about software for improved “implement-ability” versus what the vendor thinks is important for improved “sell-ability.”
  • Better manage your software selection projects to ensure smoother implementations.

Buy Now

Chapters

  • Chapter 1: Introduction to Software Selection
  • Chapter 2: Understanding the Enterprise Software Market
  • Chapter 3: Software Sell-ability versus Implement-ability
  • Chapter 4: How to Use Consulting Advice on Software Selection
  • Chapter 5: How to Use the Reports of Analyst Firms Like Gartner
  • Chapter 6: How to Use Information Provided by Vendors
  • Chapter 7: How to Manage the Software Selection Process

http://www.computerworld.com/s/article/9237117/SAP_adds_to_supply_chain_tech_with_SmartOps_acquisition

Software Category Analysis – Supply Planning

Introduction

Supply planning uses the methods of MRP, DRP, heuristics, allocation, and optimization (both cost and inventory) in order to make the recommendations of what, when and how much to bring material into the supply network, the what, when and how much to move material between the locations of the supply network, and in some applications what, when and how much create the production recommendations. Supply planning was performed exclusively in ERP systems using the twin methods of MRP and DRP up until the mid 1990s when companies began investing in advanced planning systems. These advanced planning systems used more sophisticated methods that up until that point hardware was insufficiently powerful to leverage. These applications were introduced with great fanfare, but also had high failure rates because they were generally not designed to be easily implemented or easily maintained. Applications in this category are what we refer to as first generation advanced planning products. And a number of software vendors are still selling these applications as if they are state of the art. A good marker of a first generation advanced planning applications is if it uses a cost optimizer. During the period when first generation the prevailing wisdom was that any supply chain domain could be “optimized” with by focusing on minimizing costs. Some of the advanced planning applications have still not progressed beyond this state. Optimizers are run with constraints, which limit the result to what is actually feasible.

Constraints

When used in planning, constraints limit the solution to what is feasible, or what is actionable by the business. By limiting the solution, the time and processing spent evaluating recommendations that cannot be converted in reality are also limited.

The Real Story Behind Constrained Planning

The ability to use constraints is a major differentiator between applications in the minds of buyers. However, the ability of buyers to actually implement constrained systems is much more limited. One of the important factors in how well constraint based systems can be implemented is how easily constraints can be modified and assigned – something which buyers rarely look for. The best application at managing constraints that we have seen is PlanetTogether, which is primarily a production planning and scheduling software vendor, although they are moving into supply planning. Curiously enough, while applications like SNP can hold supply planning constraints, by far the most common constraints used in supply planning are actually production constraints. Supply planning applications can be differentiated partially based upon whether they can incorporate production constraints. When they do, and when they are used, the planning system generates both the initial production plan along with the supply plan (stock transfers and purchase requisitions).  After this point, the supply plan and initial production plan are passed to the production planning and scheduling system where the more detailed planning and scheduling is performed, and adjusted, before being passed back to the supply planning system. This is the standard approach used by the supply planning applications that can incorporate production constraints. We refer to it as the sequential approach, because first the supply plan is run, then the production planning and scheduling is run. However, after several decades of working this way, our observation the standard approach is not actually effective. PlanetTogether, a software vendor we rate as the most innovative in the production planning space, are currently developing ways in which the supply plan and production plan are created in a single planning run – something which allows production to be managed much more flexibly than in the standard sequential approach.

Choosing 2nd Generation Planning Applications

Because of the numerous implementation problems with first generation supply planning systems, we tend to score applications significantly higher if they were new – which would mean being developed on new principles within the past 10 years. This is not because we are focused on newness for simply the sake of newness, but because there have been observations about what has and has not worked in supply planning, and older applications – while they may make some changes, have difficulty in being adjusted to work a more modern and effective way. In addition to the modernity of the methods used, we give significant weight to how well the system can be adopted by users. One of the highest rated applications in this category does not actually use complex methods for generating the supply plan, but is highly rated because software vendor focused on usability and maintainability. This should demonstrate our view, which we can support with project experience, that the complexity of the mathematics used to generate the supply plan is only one measurement of the application. This is actually a consistent observation across many enterprise software categories, if not all of them that complex solutions often do not lead to good outcomes.

Inventory Optimization and Multi Echelon Planning

Several of the applications profiled in this software category section use the inventory optimization and multi echelon planning (MEIO for short) method. MEIO is an innovative use of two separate forms of optimization: inventory optimization and multi-echelon inventory optimization (but which I simply refer to as multi-echelon planning to reduce confusion). MEIO applications are an example of the 2nd generation planning applications that we just discussed. While cost optimizers are generic and adapted to different supply chain planning domains, MEIO was an attempt to adjust the optimizer for the specific environment of supply planning; each component of MEIO answers a separate supply chain-planning question.

  1. Inventory Optimization: Answers the question of how much to keep in inventory.
  2. Multi-echelon Planning: Answers the question of where to keep inventory in the supply network.

Developers of MEIO applications have very smoothly combined both sets of mathematics (which were developed separately) to work in unison during a single supply planning run. Unlike supply planning techniques that use sequential processing or calculation, MEIO calculates the service level impact of carrying one additional item at every product location combination and then sorts the list of options by their contribution to service levels and selects the best contributor. It is a powerful technology that is still only understood – beyond a high level understanding – by a small portion of the people that work in supply planning. Some important concepts behind MEIO are included in the following paragraphs.

Multi Echelon Aggregate Purchasing

While most companies have multi-echelon networks, not all supply networks are of equal complexity from the perspective of multi-echelon. The more locations, and the more echelons (regional DCs, which feed DCs, which feed forward stocking locations, etc.), the more complex the multi-echelon problem becomes, and the more beneficial the implementation of MEIO software would be. Service parts networks are known for having a high number of echelons due partially to their need for forward stocking locations that can quickly service expensive equipment, thus minimizing equipment downtime. Service parts networks have the additional complexity of needing to move repairable items to locations in the supply network where they can be serviced. Therefore, it is not surprising that one of the early innovators in multi-echelon inventory optimization was MCA Solutions, a vendor that focused on the service parts market. Unfortunately they were acquired by Servigistics. Furthermore, the earliest papers on multi echelon and inventory optimization were directed towards optimizing service parts networks, not finished goods networks.  For any application to be multi echelon, it must have the concept of effective lead time – that is instead of viewing lead time as a static input, effective lead time is situational, and dependent upon other conditions in the supply network.

Effective Lead Time

In this example, the effective lead-time is the lead-time experienced by a customer at a retail location. Note the chain effect: their effective lead-time increases as the quantity demanded increases as more demand stocks out locations higher in the supply network. The numbers here are kept small in order to improve the clarity of the explanation. A key assumption is that this is a single product supply chain.  All locations carry only one product. The example above shows that that while the actual lead time stays the same between the locations, depending upon the demand vs. what is stocked at the various locations the effective lead time changes depending upon how high the multi echelon supply chain it is necessary to go to obtain inventory. Service levels can be set at various places, which vary depending upon the particular vendor. Companies that intend to select and implement MEIO software should have the necessary internal discussions as to how and where they want to control their supply planning with service levels. The way the implementing company is current performing supply planning will if unaltered, will not be able to fully leverage MEIO’s capabilities. The decision of where to set service levels should be known prior to any MEIO software selection. Of course this means understanding the options for service levels. To this end I have listed the options below. In MEIO software, service levels can be set by the following:

  1. At the location
  2. At the product-location combination
  3. At the group location
  4. At the customer
  5. At a product mix, and
  6. *At the contract/equipment

Degrees of Serice Level Control

Where the service level can be set in the application makes a very big difference in terms of how the company can use the application as well as how powerful the application is, but also in the degree of maintenance required after the application is installed. MEIO applications can be categorized partially by how easily the service level is set and how high in the hierarchy—contract, customer, location, and product location—the service level can be set

Multi-source Planning

Multi-source planning (or multi sourcing) — the ability to have the system flexibly choose from external sources of supply — has been a consistent requirement at many companies. However, many companies have also had a problem getting multi-source planning to work the way they want it to work, and so it is not implemented as commonly because of issues with functionality robustness. Buyers must do a better job of having the software vendors actually make proof of concepts with regards to multi sourcing work if the application is being partially purchased on the basis of this.

Software Category Summary

Supply planning has a hangover from the purchase and implementation of many applications, which were overly complex, and developed and implemented by software vendors more focused on sales than on implementation success. The likelihood of receiving a very good supply plan from and ERP system is low. Supply planning systems are very important to the overall solution architecture, but the best applications cannot be found from any of the name brand software vendors. To find a good supply planning application, buyers should be looking for 2nd generation applications and software vendors who have really thought through what has and had not worked in previous approachs. Supply planning software is a complex area to analyze and it’s easy to get tied up in the complexity of some of the applications. Overall this software category has a small number of compelling applications. This is an area where buyers really understand their requirements and their tolerance for complexity before even initiating a software selection.

MUFI Rating & Risk

See the MUFI Ratings & Risk below for all of the applications we cover.

Vendor NameApplication
Big ERP
SAPMUFI Rating & Risk – SAP ECC
OracleMUFI Rating & Risk – JD Edwards EnterpriseOne
EpicorMUFI Rating & Risk – Epicor ERP
SageMUFI Rating & Risk – Sage X3
InforMUFI Rating & Risk – Infor Lawson
Small and Medium ERP
SAPMUFI Rating & Risk – SAP Business One
OracleMUFI Rating & Risk – JD Edwards World
ProcessProMUFI Rating & Risk – ProcessPro
RootstockMUFI Rating & Risk – Rootstock
ERPNextMUFI Rating & Risk – ERPNext
OpenERPMUFI Rating & Risk – OpenERP
MicrosoftMUFI Rating & Risk – Microsoft Dynamics AX
Financial Applications
IntacctMUFI Rating & Risk – Intacct
IntuitMUFI Rating & Risk – Intuit Quickbooks Enterprise Solutions
FinancialForceMUFI Rating & Risk – FinancialForce
NetSuiteMUFI Rating & Risk – NetSuite OneWorld
PLM
SAPMUFI Rating & Risk – SAP PLM
Arena SolutionsMUFI Rating & Risk – Arena Solutions Arena PLM
Hamilton GrantMUFI Rating & Risk – Hamilton Grant Recipe Management
Demand Planning
SAPMUFI Rating & Risk – SAP APO DP
TableauMUFI Rating & Risk – Tableau (Forecasting)
Business Forecast SystemsMUFI Rating & Risk – Forecast Pro TRAK
Demand WorksMUFI Rating & Risk – Demand Works Smoothie
JDAMUFI Rating & Risk – JDA Demand Management
ToolsGroupMUFI Rating & Risk – ToolsGroup SO99 (Forecasting)
Supply Planning
SAPMUFI Rating & Risk – SAP SNP
SAPMUFI Rating & Risk – SAP SmartOps
ToolsGroupMUFI Rating & Risk – ToolsGroup SO99 (Supply Planning)
Demand WorksMUFI Rating & Risk – Demand Works Smoothie SP
PlanetTogetherMUFI Rating & Risk – PlanetTogether Galaxy APS Superplant
Production Planning
SAPMUFI Rating & Risk – SAP APO PP/DS
DelfoiMUFI Rating & Risk – Delfoi Planner
PreactorMUFI Rating & Risk – Preactor
AspenTechMUFI Rating & Risk – AspenTech AspenOne
PlanetTogetherMUFI Rating & Risk – PlanetTogether Galaxy APS
BI Heavy
SAPMUFI Rating & Risk – SAP BI/BW
SAPMUFI Rating & Risk – SAP Business Objects
OracleMUFI Rating & Risk – Oracle BI
SASMUFI Rating & Risk – SAS BI
MicroStrategyMUFI Rating & Risk – MicroStrategy
IBMMUFI Rating & Risk – IBM Cognos
TeradataMUFI Rating & Risk – Teradata
ActuateMUFI Rating & Risk – Actuate ActuateOne
BI Light
SAPMUFI Rating & Risk – SAP Crystal Reports
QlikTechMUFI Rating & Risk – QlikTech QlikView
TableauMUFI Rating & Risk – Tableau (BI)
CRM
SAPMUFI Rating & Risk – SAP CRM
OracleMUFI Rating & Risk – Oracle RightNow
OracleMUFI Rating & Risk – Oracle CRM On Demand
InforMUFI Rating & Risk – Infor Epiphany
Base CRMMUFI Rating & Risk – Base CRM
SalesforceMUFI Rating & Risk – Salesforce Enterprise
SugarCRMMUFI Rating & Risk – SugarCRM
MicrosoftMUFI Rating & Risk – Microsoft Dynamics CRM
NetSuiteMUFI Rating & Risk – NetSuite CRM