The opening keynote session for JDA Focus 2017 started out with their new CEO, Girish Rishi, who replaced Bal Dail in January of this year, a change of leadership that seems to represent more continuity than disruption.1 Rishi opened up Focus 2017 introducing himself and then describing JDA’s products as fitting into four segments 1) Planning, 2) Execution/Distribution, 3) Retail, 4) Edge. This last category is interesting, as it is a departure from how JDA has traditionally described their footprint. Rishi’s background2 in RFID, data collection, and home automation aligns with this emphasis on IoT and edge computing. Edge included JDA’s Flex technology platform, control tower technology, and emerging areas of machine learning, IoT, robotics, and mobility. Rishi also emphasized and described JDA’s culture and values as Results-focused, Relentless, and Teamwork-centric.
Wayne Usie, JDA’s SVP and Chief Market Development Officer, continued the theme of connecting to the edge, describing it as becoming aware in real-time of what is happening at all the relevant points of interaction in the supply chain — whether it’s a consumer making a buy decision, a ship changing course in the ocean, a shipment arriving at a DC, or an IoT-enabled piece of equipment requesting preventative maintenance for itself. His other major theme was the user experience, empowering the end users to make more informed, agile decisions with more integrated systems. These themes are embodied by JDA in things like ‘always on manufacturing,’ constraint-aware planning for intelligent fulfillment, new warehouse and store associate user experiences, and collaborative category management.
Toy Maker’s Transformation
We heard the EVP Global Development and Product Supply & Chief Supply Chain Officer for a major toy company. They own a number of their own manufacturing plants, introduce thousands of new products each year, and build tens of thousands of new molds3 each year to build those products. Theirs is a highly seasonal business with ever shorter product lifecycles and a need to respond quickly to changes in tastes and demands. Thereby they are moving to more digitized product development and digitization of the supply chain through cloud connectivity, robotics, and 3D printing.
The company felt they needed a control tower to bring together information from their disparate (and outdated) legacy systems. They said JDA invested a lot of time and effort to understand what they were trying to accomplish. They selected JDA and concluded the first phase, piloting in two factories, at the end of 2016. With this improved visibility, production adherence4 increased from 65% to 90% percent, stockouts dropped, and they reduced the S&OP cycle from monthly to weekly. Over the coming months, the toy company will roll out demand planning, master planning, MRP,5 and DRP.6 Many other enterprises felt they had to get a new ERP system in place as a foundation on which to layer supply chain capabilities. So, I found it interesting that they took the opposite approach, using the JDA implementation to lay the foundation preparing for a future company-wide ERP implementation.
‘Always On’ Category Management
Traditional 6-month assortment and planogram planning cycles are being challenged by the speed of new product introductions, changing trends, increases in SKUs, more dynamic retail spaces, and the need to squeeze every penny out of every square foot of physical retail space in an increasingly omnichannel world. As a result, the assortment-to-planogram process needs to be compressed. One of JDA’s customers said they are looking to go from a 22-week cycle down to 12 weeks. Another is aiming for 8 weeks.
The traditional calendar-based approach is too slow to meet these ultra-fast response times. To get there, JDA is developing ‘Always On, Cognitive Category Management.’ This involves continually monitoring changes to current and predicted behavior of consumers. Prescriptive analytics are used to do simulations and optimization and continually enhance performance via what JDA described as a ‘Test and Learn’ framework, to tailor optimal assortments across stores. Machine learning is used to identify the customer’s unmet needs (such as demand that would have materialized if the right inventory was there), optimal merchandising strategies, pricing decisions based on product attributes and price elasticity, and ranges tailored by store and format. This encompasses several elements: traditional business intelligence (what happened/what is happening), combined with business rules and constraints (inventory policies, days of supply, case pack minimums, etc.), and predictive analytics about future behavior, such as which products tend to be purchased together, which attributes drive margin, and so forth. On top of all this capability, JDA is developing a ‘Cognitive Category Management Dashboard’ for business analysis. Eventually, they will use IBM’s machine learning, to learn from the decisions of the merchandisers that are getting the best results, in order to make recommendations for future decisions.7
JDA’s Partnering Machine Revs Up
JDA has a deep, rich, and broad portfolio of supply chain capabilities and IP, developed over the past 25 years. But they also recognize the advantages of partnering with companies, both as channel partners, and for extending their ecosystem footprint with unique technology. They have made some significant strides in their partnering program during the past year, culminating in the announcement at Focus of their Partner Advantage Program. There are three types of partners in the program: 1) Selling Partners — who directly sell, or refer, or co-sell with JDA, 2) Management consulting and IT consulting/system integration firms, 3) Technology Partners that enhance and complement JDA’s offerings with hardware and software solutions.
JDA implemented a new SaaS PRM (partner Relationship Management) system, which includes a partner portal with sales and marketing tools, opportunity registration, price request, training programs and plans, and more. They have developed simplified, templated, standardized contracts with more automated back office functions to expedient transaction processing. For the first time, JDA has a Partner Expertise program with testing and accreditation on a per employee level, to represent partners’ expertise and demonstrated knowledge around JDA solutions.
Partners will be in Bronze, Silver, and Gold categories with specifically stated requirements for each tier based on 1) Amount of JDA revenue stimulated, 2) Number of accredited professionals, and 3) Sponsorship to build awareness and incremental demand. There are increasing benefits for partners as they move up the tiers, such as market development funds and executive sponsorship. JDA is offering co-branded collateral that partners can personalize and use with their own direct marketing.
Expanding Key Technology Partnerships
JDA highlighted several key technology partnerships demoed at the show, including:
- Always On Manufacturing — in partnership with TransVoyant, provides real-time visibility and precise ETA (estimated-time-of-arrival) information for products and shipments, anywhere in the world, alerting planners about delays and giving suggested corrective actions, such as rerouting of inventory.
- Warehouse of the Future — in partnership with Kenco (3PL), demoing the use of drones in a warehouse to scan inventory.
- Store Optimizer/Dynamic Merchandising — via their Intel partnership, provides near real time inventory visibility and optimizes in-store tasks to reduce out-of-stocks, improve labor productivity and increase customer satisfaction.
JDA announced a significant partnership with with dunnhumby, the consumer data science company. Dunnhumby has more than 500 data scientists, analyzes 44 billion shopping baskets in excess of $600B in retail sales, representing the voice of the customer for over 800 million shoppers. JDAhas entered into an agreement to jointly build new software using dunnhumby’s proprietary algorithms and IP connected to JDA’s platform and applications. This will help personalize and tailor assortments by store, get pricing and promotions right, and provide personalized offers and promotions. Machine learning will be leveraged to identify consumer preferences across all merchandising decisions. Dunnhumby and JDA will start by focusing first on assortment, space and localization. After that, they will work on assortment optimization, then eventually macro space planning. I pointed out the similarities between this initiative and what JDA has been trying to do with Retail.me through JDA Labs. They said this initiative will accelerate those efforts.
The concept of Flowcasting has been around for a long time. Typically, retailers and their suppliers develop separate forecasts for the same end demand. The retailer may even have multiple internal forecasts — one for sell through, another for store replenishment, and a third for DC replenishment. Suppliers build a forecast based on the expected order flow from the retailer. CPFR8 attempts to bring retailers and suppliers together to pool their knowledge and reconcile those forecasts. With Flowcasting, there is only one forecast, and that is at the shelf/POS; what will actually be sold at which locations/channels. Everything else is calculated from that shelf/item-level forecast, based on lead times, existing inventory, optimal pack and shipment sizes, and other factors.
However, Flowcasting has been painfully slow to take off. JDA probably has more experience than any other vendor in helping customers with Flowcasting. As a result, they have understood that looking at the ideal end-to-end implementation of Flowcasting, from the shelf all the way to the factory, is a daunting task — a ‘boiling the ocean’ proposition. So, they have been working on breaking it down into incremental steps and embedding these capabilities into existing tools and workflows that their clients are already doing, such as:
- CPFR — using Flowcasting to develop a joint plan visible to both parties. The plan is not just the forecast, but a joint promotional plan, and both unconstrained and constrained supply plans. This is delivered through JDA’s Collaboration Workbench, which helps parties collaborate on categories at an aggregate level, drilling down by region to store and item levels.
- Action-oriented Supply Chain Analysis — predictive analytics to monitor for exceptions, and then alert and recommend actions to retail planners. JDA has algorithms that tell if there is an out-of-stock or overstock situation, and helps with root cause analysis, such as whether a promotion is underperforming due to delays in shipments from the supplier, or execution issues at the stores. The system can make recommendations, such as adjusting safety stock levels. It also provides simulation capabilities.
- Prescriptive Scenario Analyzer — using a probability of demand realization, rather than a point forecast, the system can describe the level of confidence in the forecast and the probability of demand being over or under, to allow planners to create end-to-end planning playbooks for low, mid, and high demand scenarios. Planners can run simulations and a prescriptive scenario analyzer to assess impact on KPIs.
- New Product Introduction — an NPI9 dashboard shows how things are progressing, highlighting issues, and letting the planner play ‘what if’ scenarios, to compare different courses of corrective action and their impact on various operational metrics.
The idea is to simplify the job of a planner. Flowcasting can often start within a single enterprise to unify forecasts around their end demand. The Flowcasting tools sit on top of and are integrated with these workflows that are already being done.
JDA as Innovation Hub/Engine
A recurring theme for JDA is their commitment to innovation. This is demonstrated with results from JDA Labs, the kinds of partnerships they have, and the depth of IP they continually develop. They pointed out that JDA has over 300 patents awarded, plus over 100 more pending, and they are filing on average a new patent per month. My experience has been that every time I meet with JDA folks, they are working on something new, exciting, and differentiated. Their partnership efforts should serve to accelerate this. JDA has a portal for submitting new ideas that can come from anywhere across their entire organization, from partners, and from customers. This is the top of their ‘innovation funnel’ from which they prioritize those efforts that will make the biggest impact. Some are simple enough to go straight into the product. Others they may prototype and fail fast, co-innovating with customers when it is warranted, moving the best ideas from concept to production as quickly as possible. My impression from Focus is that JDA’s employee morale is solid, and the company is a place people are still excited to work at. We look forward to seeing where they go next.
1 Employee morale improved markedly under Dail, so I was wondering what they thought of the new leader. “So far, so good” seems to be the attitude amongst the employees I queried. — Return to article text above
2 Rishi was from RFID pioneer Matrics, AIDC leader Symbol, Motorola, and most recently leading Tyco International’s retail solutions and home automation businesses. Tyco retail solutions has EAS (electronic article surveillance), RFID, traffic counting, video analytics, and other store sensing and software solutions. — Return to article text above
3 For both injection molding and die casting. — Return to article text above
4 This means adherence to established, approved Standard Operating Procedures (SOPs). — Return to article text above
5 MRP = Material Requirements Planning — Return to article text above
6 DRP = Distribution Resource Planning — Return to article text above
7 For more on this topic, see JDA’s white paper, The Future of Category Management: Top Trends for the Next Decade — Return to article text above
8 CPFR = Collaborative Planning, Forecasting and Replenishment — Return to article text above
9 NPI = New Product Introduction — Return to article text above
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