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In today’s customer-centric business environment, it is imperative to have the right stock available at the right place, at the right time, and at the right price. This is a perpetual challenge that many Retailers face considering the fast pace and challenges of the retail business. Most Retailers today use an omni-channel presence with an integrated strategy to engage their customers. However, it is also important that retailers have an effective assortment optimization strategy to ensure effective customer engagement, whether online or in-store. Each strategy requires careful calibration to achieve category goals, and assortment strategies vary based on the different merchandise categories.

Introduction to Assortment Optimization case:

is up to the user to collaborate and find out deviations in the existing merchandise and assortments plans, as well as analyze the business impact, before creating a strate-gic response to deal with the situation. Suffice it to say, existing approaches are inadequate for continuous assortment optimization.

More specifically, drawbacks include:

• No incorporation of broader set of customer and market centric factors that influence the demand

• Increased cognitive burden for Merchandisers and Category Managers

• Higher risk of expensive errors and omissions because of complexity of assortment planning and cognitive biases

• Inability to react to events in real-time lead to loss in potential revenue

Category Management teams and the Store Operations Management teams need to sense opportunities well in advance, in order to understand the potential impacts to their business compared to industry expectations. If a system were able to provide a business validated strategy, and preempt a potentially adverse situation, it would save from potential revenue losses, or uplift sales, or even acquire a new customer. Business users would also prefer to be notified of business situations that require their immediate intervention in real-time not after the matter.

Today’s Retailer expects information systems to be cognitive, intelligent, and self-learning. The industry needs an opportunity-driven model to ensure timely action, and to optimize business processes on a continuous basis. Existing Merchandise Assortment Planning (MAP) applications have evolved in their usefulness and utility over time. Nevertheless, while most applications provide tools to provide insights for decision-making, the actual decision-making itself is left to the user. Users have to review various planning KPIs, and make decisions after reviewing multiple planning sheets across categories. It

Industry Expectations

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Inventory DistortionAssortment Optimization

DIWO® SENSE:

How DIWO® helps with Assortment Optimization:

DIWO® senses opportunities before they arise, and presents them to business teams with details about the opportunity, the impact to revenue, and the recom-mended strategy to address it

SENSE

EXPLORE

ACT

LEARN

DIWO® makes recommendations for the business opportunity it senses and allows the business user to optimize the strategy based on DIWO®’s deep insights and analytics.

DIWO® provides a targeted action list to guide business teams as they imple-ment the recommendations.

DIWO® assimilates learning from decisions and actions.

Merchandise Plans and Assortment Plans are formula-ted for upcoming seasons based on a combination of current market trends, and the performance of catego-ries the previous year. This is done to ensure that product assortment stays fresh and in vogue with customer expectations. Merchants plan their category objectives in terms of the sales and gross margins across the enterprise, and evolve strategies to achieve those set targets. Given the complexities of retail and ever-evolving customer expectations, merchants often need to revalidate their existing plans at strategic intervals throughout the season, and recalibrate them if necessary. DIWO®’ s opportunity driven model helps solve the uncertainty and complexities of Assortment Optimization by using DIWO® SENSE. The crux of the DIWO® platform is the Continuous Business Optimiza-tion mode. DIWO® SENSE continuously monitors real time data indicators and other extraneous events to identify any deviation from plan, and therefore recalibra-te retail plans to achieve category goals.

DIWO® monitors streaming POS data to compare actual sales with planned sales to look for any unexpec-ted deviation in buying behavior. If this deviation is above a certain threshold and looks like it will persist until the next decision period, then it is further analyzed. DIWO® SENSE also tracks for product affinity changes that might influence future buying behavior.

DIWO® SENSE monitors a variety of events that might have an impact on buying behavior in the oncoming decision period. Examples of events include: sudden change in weather pattern, sudden shift in buying trends as gleaned from the market data, competitive pricing events, recall of products, new product launches, any social event which might impact the sales in a geogra-phy, etc. For each event type monitoring, DIWO® predict its impact on sales. If the newly predicted sales deviate from the planned sales beyond a pre-specified thres-hold, DIWO® proceeds to the next step for further evaluation.

DIWO® will compare the category contribution mix percentage to the planned contribution, and see whether category goals for sales and gross margin have been met. The categories that show deviation are tracked for further analysis. Deviation can go both ways. Some categories may have under-performed, while others may have exceeded their category targets. Depending on the remaining time frame left in the season, and the forecasted demand, DIWO® will recommend either an increase or decrease in allocation for category styles. This will ensure that overall category numbers are maintained. The SENSE cognitive thinking allows DIWO® to distinguish between temporary blips in sales, or a persistent trend.

DIWO®’s cognitive solutions platform is based on a data analytics system for processing big data with built-in modules to handle data streaming, machine learning, and graph processing. DIWO® is able to integrate with the retailer’s enterprise data solutions/ERP, data warehouse and other downstream applications to glean actionable insights from the underlying data. It can integrate with third-party applications on weather, sentiment analysis, and syndicated data from industry. DIWO® presents SEAL, an opportunity-driven business optimization methodology, to solve today’s business problems. DIWO is a cognitive platform solution using the most advanced parallel processing technologies to aid smart decision-making. SEAL stands for:

Diwo Introduction...

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DIWO® EXPLORE:

While DIWO® runs, DIWO® EXPLORE has already gone through tens of thousands of business strategy possibili-ties and is ready with the most optimum strategy for the business user to implement and prevent revenue losses. Strategies have been evaluated on the basis of short-term and long-term effects on the business situation. As a part of this module, DIWO® lets the business user analyze the strategy and presents multiple insights and ‘What if’ analysis to understand the situation better. It runs strategies to optimize the category mix to ensure that trending products have a higher contribution mix versus the non-trending product categories. It analyzes whether an enterprise level change is required in the assortment plan or whether the optimization is only required at an individual store level. Any change to the Merchandise plan entails a change in the model stock quantity plan across the Store Tier. DIWO® EXPLORE analyzes the updates required at each individual store level to ensure a profitable mix. Any inventory distortion at the stores could lead to an under stock or an overstock situation leading to a revenue impact. This in turn leads to a decrease in the gross margin of the category across the enterprise. As a result, it is imperative to ensure an optimized stock holding.

Demand forecasting is done for all products within the selected Categories across all stores. Demand forecas-ting considers different aspects of weather, external events, demographic constraints, product attributes etc. to arrive at a correct forecast. Current and emerging customer and product trends are considered to accurate-ly determine the demand forecast. New forecasted numbers are then aggregated for the product at different level of the time and location hierarchy. Forecasted demand is validated with the existing Stock on Hand (SOH) to ensure viability of the projected numbers. DIWO® will pinpoint the exact products/SKUs that require a change in the model stock plan by analyzing the assortment depth and width effectiveness. Using the bottom up approach, DIWO® will aggregate the numbers from the SKU level at individual store to forecast the numbers at the Category level from a quantity perspecti-ve, which can be translated to a sales dollar value. Business users can customize the strategy by changing the lever for demand quantity on the model stock plan, based on the What If analysis. For any customization done, the revenue impact will be recomputed, and the Category Mix percentage will be impacted.

DIWO® EXPLORE provides rich graphical visualization of various operational scenarios using important KPIs. It allows the business users to understand the impact of Product attributes like color, size, price points, etc., on his or her products. It lets the user understand the customer

profiles of the people buying those particular category products.

Users can create multiple such strategies and can compare these strategies with each other to decide the most optimum strategy.

DIWO® ASK

DIWO® ASK offers a guided goal-oriented ability for DIWO® to interact with business users in natural langua-ge conversation. Business users can simply ask ques-tions related to Retail KPI Metrics of Sales, Planned Sales, Forecasted Sales, Stock On Hand, In Transit Orders, Open Orders, Sell Through Percentage, Stock to Sales Ratio, Gross Margin, GMROI, FWOS, etc. Users can have a conversation with DIWO® in a question and answer mode, while also going deeper into areas. The DIWO® ASK persona learns from the conversational style of the business user and is able to relate context to the user while framing the answers.

2/15/2016

We have considered all Stores in your assigned Region. To narrow down results, please filter by Region and Store

Related Questions

What are the categories for these SKUs?

What are the categories for these SKUs?

Show me all SKUs in Apparel with Inventory agegreater than 90 day

We have 20 SKUs with Inventory Age greater (>) than 90 days. Inventory of these SKUs is 8.3% of the Department Inventory and 0.8% of the Total Inven-tory.

Product SKU Category Aged Units Revenue Loss

33% Aged Inventory10% Threshold

SKU #2356

00000

00000

00000

00000

00000

00000

00000

00000

00000

Cat. #3

Cat. #3

Cat. #3

Cat. #3

Cat. #3

Cat. #3

Cat. #3

Cat. #3

Cat. #3

13

398

97

90

89

76

54

43

90

$3,678

$3,009

$2,893

$2,598

$2,345

$1,897

$1,527

$1,455

$2,598

SKU #11111

51%Age 0-30

Age 31-605%

Age 61-90

0%Age >180

100%

0 %Aged Inventory Avg. aged InventoryThreshold

DIWO® LEARN

DIWO® LEARN is the cognitive strength of the system

1. Replenishment Transfer

2. Implement Markdown Strategy

Store #15

Revenue Impact

Gross Margin

$ 12 K

48% 29%

FWOS

Season End

17 weeks

4 weeks

Identified

Impact

Dec 22 /2015

Jan 10 /2016Curved Clutch

SKU 7441919236

Opportunity #138 Store #32Excess Stock

1. Inter-Store Transfer

2. Substitution

Store #15

SKU 5841982285

Revenue Impact

Customer Loss

$ 15 KFWOS

ADS

0.4 weeks

12 weeks

ODS Dec 21/2016 - Dec 24/2016

Identified

Impact

Sep 20/2016

Dec 24/2016

Opportunity #137 Store #26Out Of Stock

10%Base Product:

Substitute Product:

!

03/04

used to assimilate the lessons learned from opportuni-ties and the actionable steps taken. At each step of the SEAL process, DIWO® is learning from the recommenda-tion and the subsequent actions taken using Machine Learning techniques. This 360-degree feedback is considered when a similar situation arises for Excess Stock in the future. Over time, DIWO®’s cognitive engine keeps improving its decision-making ability and is able to accurately predict and provide recommendations that are practical and tested in the business domain.

KnowledgeBase Growth

SenseSpeed

PredictionAccuracy

RevenueRecovery

RevenueRecovery