Nine Technologies Transforming the Supply Chain, Part 3

Stephen DeAngelis

October 5, 2012

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

 

Analytical In-Memory DBMS

 

The staff at Supply Chain Standard notes that an In-Memory Data Base Management System (IMDBMS) “is a DBMS that stores the entire database structure in memory and accesses it without the use of input/output instructions. [“Nine technologies will transform supply chain over coming decade,” 5 September 2012] It continues:

“Analytical IMDBMSs focus on addressing analytical needs — leveraging the high speed of in-memory capabilities. Technologies include in-memory column-store DBMSs and in-memory massively parallel processing row-store-based technologies. Tim Payne, research director at Gartner, said the speed of IMDBMS for analytics has the potential to simplify the data warehouse model and reduce maintenance by removing the need for aggregates, summaries and cubes. This would result in lower administration costs and offer greater agility in meeting analytical requirements.”

The staff at EBMS2 writes, “An in-memory DBMS is a DBMS designed under the assumption that substantially all database operations will be performed in RAM (Random Access Memory).” [“In-memory, (hybrid) memory-centric DBMS — three analytic glossary draft entries,” A Monash Research Publication, 20 August 2012] The article continues:

“Ways in which in-memory DBMS are commonly different from those that query and update persistent storage include:

    • Data access processes which include a larger number of individually cheaper steps. In-memory database access is orders of magnitude cheaper than disk access, so it’s not as important to minimize the number of accesses.

Reduced locking. At RAM speeds, the cost of database locks can be significant, so in-memory DBMS are designed to minimize their use.

“… Even true in-memory DBMS may copy data into persistent storage, so as to keep it safe. Examples of in-memory DBMS include:

  • SAP HANA.
  • Oracle TimesTen.
  • IBM TM1.
  • Several NewSQL systems, such as VoltDB.
  • Several NoSQL systems, such as Citrusleaf.

Payne told the Supply Chain Standard staff, “Some technologies, such as columnar IMDBMSs, have the opportunity to grow beyond analytical use cases into transactional processing and, as a result, enable new applications that were previously difficult to implement due to latency issues between the transactional and analytical environments. These applications could be transformational — by driving new business opportunities and processes.”

 

Demand Signal Repository

 

Wikipedia describes a Demand Signal Repository this way:

“Demand signal repository (DSR) is the process whereby consumer goods companies integrate and cleanse demand data, and leverage that data to service retailers and end customers efficiently. Cleansing it and synchronizing it with syndicated and internal data allows companies to provide business users with a more complete view of their sales. The repository itself is a database that stores the information in a format that allows for easy retrieval of information so that users can easily query the database to identify what’s selling, where, when and how. Identifying Out-of-Stock’s (OOS’s) is a requirement. Leveraging that data to perform predictive analytics is where applications actually leverage POS [point of sale] within their data model to help identify both current and potential impact.”

Teradata is one of many companies that offer a Demand Signal Repository. To watch a two-minute Teradata video that describes what a DSR can do for a business, click on this link. Wikipedia continues:

“With the right architecture, a DSR will grow with the business needs. It will be leveraged across multiple business groups including category management, supply chain, inventory management, promotion and event management, sales, marketing, etc. Users should be able to use any tools needed for their specific job requirements. If they can’t, then you have a point solution that is proprietary and not a true DSR. An open architecture should have a nice user interface that lets users easily get reports to help them understand their sales, manage category and brand information, etc. Users should easily be able to drag, drop and drill into information. They should be able to pull data from multiple data sets, share reports securely, create alerts, etc. In addition, users that have specific job requirements, such as price elasticity or analyzing promotional ROI, etc. may have a specific tool they need to use which leverages POS data. A properly designed DSR will allow other tools (in addition to their own tool) to leverage POS data. Alerts will pin-point areas of the business that require immediate attention. The goal of a DSR is to provide faster access to more information, improve retailer relationships, maximize ROI, streamline internal efficiencies, improve performance at all stages of the supply chain and support multiple departments and teams.”

Steve Banker insists that “the vocabulary used to describe these types of products is not very good.” He provides a good discussion of this problem in a post entitled How to Best Describe Demand Signal Repositories. Despite any semantic confusion, Payne is correct that this capability will play an important role in the supply chain of the future.

 

Geographic Information Systems for Mapping, Visualization and Analytics

 

Fabrizio Brasca, vice president for global logistics at JDA Software, reminds us that there is a lot of truth in the old saying, “A picture is worth a thousand words.” [“Next Generation of Visualization and User Interaction,” Logistics Viewpoints, 6 September 2012] Brasca reports that at a recent conference he attended at MIT “there was one particular view that emerged consistently at the forefront of everyone’s mind. The issue was visualization and usability.” I have repeatedly noted in the past that information that is presented in way that is difficult for users to obtain or understand is little better than having no information at all. Payne claims that Geographic Information Systems (GIS) should be high on list of ways that companies improve visualization.

 

GIS provides geographic visualization and “refers to a set of tools and techniques supporting geospatial data analysis through the use of interactive visualization. … GIS and geovisualization allow for more interactive maps; including the ability to explore different layers of the map, to zoom in or out, and to change the visual appearance of the map, usually on a computer display. Geovisualization represents a set of cartographic technologies and practices that take advantage of the ability of modern microprocessors to render changes to a map in real time, allowing users to adjust the mapped data on the fly.” [“Geovisualization,” Wikipedia] GIS have been used with great effect in areas as diverse as healthcare, crime prevention, and urban planning. I agree with Payne that these tools can be put to good use in the supply chain field.

 

For example, a company called Decision Analyst discusses on its website how it can help companies through the use of GIS. It states, “Using GIS, we incorporate proprietary performance metrics along with demographic and economic information and our proprietary real estate databases.
… These maps provide an effective visualization and immediate understanding of strategic market opportunities. The kinds of information that can be mapped:

 

  • Competitor analyses
  • Trade or coverage areas
  • Customer locations and profiles
  • Demographic variables
  • Franchise encroachment
  • Industry guides
  • Industry influences
  • Market analyses
  • Profit analyses
  • Sales revenues
  • Sales territory analyses
  • Sales territory balancing
  • Served/Underserved clients
  • Service areas
  • Service needs
  • Service territories
  • Site analyses
  • Target market analyses

 

As with most of the technologies identified by Payne, it doesn’t take much imagination to see how useful GIS could be for businesses. All in all, Payne did an excellent job identifying technologies at the peak of their “hype” along with 52 other technologies worth keeping an eye on. Clearly, technology will dramatically change how supply chains function in the future.