In yesterday’s post, I discussed the first three of nine technologies identified by Gartner analyst Tim Payne that he claims are poised to transform supply chain management. [“Hype Cycle for Supply Chain Management, 2012,” Gartner, 27 July 2012] They were: Integration Platform as a Service (iPaaS), Master Data Management (MDM) of Supplier Data Solutions, and Multienterprise Business Process Platforms. In this post, I’ll discuss the next three technologies identified by Payne: Price Optimization, Process Templates, and Software-as-a-Service Supply Chain Planning. Tomorrow I’ll discuss the final three technologies: Analytical In-Memory DBMS; Demand Signal Repository; and, Geographic Information Systems for Mapping, Visualization, and Analytics.

Price Optimization

Bain & Company notes, “Price Optimization Models are mathematical programs that calculate how demand varies at different price levels, then combine that data with information on costs and inventory levels to recommend prices that will improve profits.” [“Price Optimization Models,” Bain & Company Guide, 13 December 2010] The Bain Guide continues:

“The modeling allows companies to use pricing as a powerful profit lever, which often is underdeveloped. Price Optimization Models can be used to tailor pricing for customer segments by simulating how targeted customers will respond to price changes with data-driven scenarios. Given the complexity of pricing thousands of items in highly dynamic market conditions, modeling results and insights helps to forecast demand, develop pricing and promotion strategies, control inventory levels and improve customer satisfaction.”

The staff at Supply Chain Standard writes, “Price optimization enables B2B companies to maximize profitability through the analysis, optimization and implementation of the complex pricing processes and governance supporting sales activities.” [“Nine technologies will transform supply chain over coming decade,” 5 September 2012] It continues:

“‘A price optimization initiative can deliver business impact in three areas,’ said Payne. ‘Firstly, it can improve margins and increase profitability by analyzing costs, customer buying behaviors, competitive activity, demand signals and historic data. Secondly, aligned with sales operations, customer relationship management applications and internal change management, price optimization can ensure a consistent customer experience both globally and across any buying channels that customers choose to use. Finally, price optimization should ideally be able to identify new selling opportunities with existing or former customers by analyzing historic and current buying patterns, order volumes and purchasing patterns.'”

Analysis of “historic and current buying patterns, order volumes, and purchasing patterns” needs to be complemented by predictive analytics. Because price optimization is so complex and, obviously, involves big data, cloud computing and advanced analytics are essential services for price optimization.

Process Templates

Gartner defines process templates as “an overarching term that describes prebuilt business process design, execution and management artifacts that accelerate time to solution. They are also known by various names, such as ‘solution frameworks,’ ‘solution templates,’ ‘solution kits,’ ‘starter kits,’ ‘process accelerators’ and ‘process pods.'” [“Process Templates,” Gartner IT Glossary] The Glossary definition continues:

“Process templates are available from application and middleware vendors as well as from consulting and system integration (C&SI) companies, outsourcing firms and cloud service providers. Typically, process templates are graphical and are based on process flows, rules or service-oriented architecture (SOA). The contents vary dramatically by provider. Some offer simple visual process models that are useful in jump-starting discussions about target processes for improvement. Others provide prebuilt detailed process models, technical reference models, candidate service definitions, technical service libraries, rule sets, user interface templates, simulation scenarios, recommended governance policies, delivery and deployment guides, and process improvement methodologies.”

RFF Electronics notes that “process mapping consists of three different kinds of charts”; namely: relationship maps; cross-functional maps; and process flow charts. The company explains:

• “Relationship Maps show the overall view. They show the departments of an organization and how they interact with suppliers and customers.
• “Cross-functional Maps or Swim Lane Charts show which department performs each step and the inputs and outputs of each step. These maps have more detail than a relationship map but less than a flowchart.
• “Process Flow charts or Process Flow Diagrams take a single step from a cross-functional map and expand it to show more detail. Process flow charts and process flow diagrams are the same thing.”

The following chart created by RFF Electronics shows a notional Cross-Functional Process Map.

The article also states, “Maps and flowcharts help people understand a work process. They make the tasks, interfaces, inputs, and outputs more visible. Analyzing a process map may help reduce cycle time, reduce costs, and increase productivity.”

Software-as-a-Service Supply Chain Planning

IBM notes, “Software as a service (SaaS) is a software model with applications centrally hosted in a cloud computing environment and accessed by users over the Internet. Many business applications use SaaS as a common delivery model because of its ability to help reduce costs and simplify deployment.” [“Software as a service (SaaS)“] Most companies have recognized the benefits of the SaaS model. Payne asserts that when this model is applied to supply chain planning it will transform how planning is accomplished. He writes, “Supply planning has had poor press in the last few years, with the focus of planning initiatives firmly on the area of demand planning and sales and operations planning (S&OP).” [“New Supply Chain Planning Model Highlights Three Key Phases,” Gartner, 25 June 2012] He continues:

“Oftentimes, companies are not able to realize the expected level of benefits from their investments. Although S&OP does include an element of supply planning, it rarely goes beyond basic rough-cut capacity planning, and/or aggregating replenishment and manufacturing plans out of operational SCP systems. As far as operational supply planning goes, we have long been in the realms of adding more optimization to try to come up with an optimal plan to meet the demand signals coming from demand planning.”

Payne reports that surveys repeatedly reveal that companies are dissatisfied with their current planning processes. He goes on to state, “To provide the right type of capability for supply chains today and in the future, the way we think about supply planning has to change, as do the tools that support planning.” He continues:

“Gartner believes the best way to think about SCP is to categorize into the following three areas the different capabilities a company needs to have in place to effectively plan for global, unpredictable supply chains:

Respond — This relates to the convergence of planning and execution, and includes the capabilities that allow a company to respond to execution and plan changes in a fast and profitable way. With effective respond capabilities, a company can assess and react to changes within the context of its chosen priorities and strategies, as well as within the overall framework of the optimized plan. This also helps to minimize the amount of nervousness that is fed back to the optimized plan. The time horizon for respond is from zero to two or so weeks, depending, for example, on customer lead times.

Optimize — This relates to the creation and evaluation of optimal plans with the context of the company’s current operating model. This is the traditional stamping ground of SCP tools, but with a strong focus on the financial impact (such as profitable demand response) of the optimized plan. The time horizon for optimize is from the end of the respond time horizon out to the midterm. It usually stretches out to the cumulative lead time of the supply chain. The optimize phase lasts up to the point where the current operating model can be flexed (for example, more overtime in manufacturing, additional shifts in the warehouse and switching supply between dual sources).

Design — This relates to the creation and evaluation of different supply chain configurations and designs. By explicitly designing the supply chain (using a segmentation approach to design a portfolio of supply chains, for instance) to a specific performance window, and then aligning the appropriate customers, products and services with the right supply chain design, a company can reduce the effective stress on a particular supply chain. The subsequent optimization of this supply chain is then easier, courtesy of the closer match between the defined customer/product attributes and the specific supply chain performance capability. In effect, you are asking less of the optimize stage to find the optimal plan.

“… A company needs to decide what level of capabilities it requires in each of these categories, from both a process and technology perspective, to support its planning needs now and in the future.”

He also believes that these capabilities should obtained using SaaS solutions. The three technologies discussed yesterday could all help a company work from a single version of the truth (i.e., a common data set). The three technologies discussed today build on that foundation and help companies align disparate divisions toward a common goal. Tomorrow I’ll discuss the final three technologies identified by Payne, namely: Analytical In-Memory DBMS, Demand Signal Repository, and Geographic Information Systems for Mapping, Visualization and Analytics.