WEBINAR. BUSINESS ANALYSIS FOR ANALYTICS IN RETAIL By: Taranjeet Khanuja : Principal Consultant HCL BUSINESS CONSULTING

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1 WEBINAR BUSINESS ANALYSIS FOR ANALYTICS IN RETAIL By: Taranjeet Khanuja : Principal Consultant HCL BUSINESS CONSULTING

2 Agenda RETAIL INDUSTRY - WHERE IS IT HEADING WHAT IS SHAPING THIS INDUSTRY ROLE OF ANALYTICS FOR STRATEGIC ADVANTAGE ROLE OF BA FOR ANALYTICS IN RETAIL INDUSTRY QUESTION & ANSWERS

3 RETAIL INDUSTRY - WHERE IS IT HEADING A LOOK AT GROWTH PROSPECTS OF THIS INDUSTRY In 2013, retail was sized at $ 21 Trillion In 2018, this increased $ 25 Trillion By 2020, the industry will touch $ 28 Trillion THE SIZE OF RETAIL INDUSTRY IS ONLY INCREASING YEAR ON YEAR *

4 THERE IS RETAILER AT EVERY STAGE HELPING CONSUMER GET WHAT THEY WANT From selling Groceries, healthcare products, electronics To selling services like Saloon and Gym memberships THE INDUSTRY IS SHOWING POSITIVE GROWTH SIGNS BUT AT SAME TIME UNDERGOING MASSIVE TRANSFORMATION AS TECHNOLOGY & GROWING IMPORTANCE OF DATA TAKES CENTERSTAGE IN ITS TRANSFORMATION IT BECOMES IMERATIVE FOR BUSINESS ANALYSTS TO BE A PARTNER IN ITS GROWTH

5 HOWEVER THERE ARE CHANGING MARKET DYNAMICS, THAT FORCES TO RESHAPE THE RETAIL INDUSTRY THE COMING OF MILLENNIALS CHANGE IN DEMOGRAPHICS AND DEMAND PATTERNS RISING DISPOSABLE INCOME RISING CONSCIOUSNESS OF ENVIRONMENT 70% prefer a personalized experience 80% are influenced by price 92% are on at least 1 social media platform. 80% own a smart phone Change in consumption pattern, choice, varied lifestyles is creating niche market segments Market Segment within Market segment: Means adoption of tailored market strategy Rising income: Means more demand for consumption Rising aspiration to have better standard of living across the age groups Increased demand of environmental friend products Increased awareness of recycling used products 60% make product recommendations & express opinions

6 AND THERE ARE DISRUPTIVE MARKET FORCES, THAT TOO RESHAPES THE INDUSTRY Force : CUSTOMER PREFERENCES driving Retail Paradigm shift Force : INTERNAL CHANGES to attract customer & increase efficiency CHANGING CUSTOMER NEEDS Flexibility of shopping Ease of shopping Comfort of shopping Efficiency in fulfilment Ease of Procurement Reduced inventory EVOLVING INTERNAL CHANGES Option to customize Attractive store exp ce DISRUPTION IN RETAIL INDUSTRY

7 COUPLED WITH THE EVOLUTION OF EMERGING TECHNOLOGIES Mobile Mobile shopping, Mobile payments, location based promotions Omni Channel Retail Shop online pick from store, shop online deliver home IOT Real time delivery tracking, in-store virtual assistant, inventory accuracy AI Robot based store operative, smart temperature control, drone based delivery Virtual Reality Smart mirror, virtual shopping, interactive instore experience The emerging technologies not only complement both the forces but creates a 3 rd force that pushes retailer to adopt them to improve efficiencies, increase market share, increase store footfall etc.

8 But Why Understanding These Forces is Important Subject for Our Discussion

9 BECAUSE ALL THESE FORCES ARE EITHER DRIVEN BY OR GENERATE THAT ONE THING WHICH EVERY RETAILER WANTS TO HARNESS DATA

10 AND ANALYSIS OF THIS DATA IS IMPORTANT BECAUSE Determine INSIGHTS in a Retailer s Organizational silos Identify CRITICAL RETAIL TRENDS Retailers plan to focus on data analytics initiatives in improving : Source : monetate.com Bring out PATTERNS over a period of time WHY RETAILER NEEDS DATA ANALYSIS Make QUICK DECISIONS through visualizations View patterns in sales from a BIRD S EYE view to DETAILS Generate PREDICTIONS based on historical data

11 Retailers derive data for each subject & use analytical tools to analyze The changing market dynamics is identified by retailers from various sources: Social Media (Market sentiments) Govt records Academic research Competition (Annual reports) Using this data they take actions: Identify new market opportunities Recalibrate brand positioning Identify market trends and make predictions Acquisitions, spin-offs required To understand customer preference changes, the retailers derive data from: CRM (Customer master, Marketing, Sales, Payment, Order management) Using this data they answer: What products customers are preferring? From which channels do they prefer to buy? To bring internal efficiency the retailers derive data from: Social media At what time do they buy most? Which promotions drive maximum sales? ERP (Inventory, Order fulfillment, Procurement) Using this data they answer: What is the optimal qty of products to hold in inventory Which SKUs to keep & decommission The emerging technologies generate data from: Warehouse Control systems, Dispatch What is right loc. for warehouse Which vendors cause delays IOT Sensors (Temperature, store footfall, low inventory) Using this data they take actions: Detect fraud Send cognitive response to customer Mobile (proximity to store / product) Regulate temp for perishable products Send promotion based on location

12 THE ROLE OF ANALYTICS Analytics plays a huge role in supporting retailers against these forces, involving MULTIPLE STREAMS OF WORK DETERMINE Objective FRAME the question EXPLORE modeling options (tools, subject areas) DETERMINE data sources & resources VISUALIZE findings and make decisions Each of these stream of work requires someone who can: Acknowledge BUSINESS OBJECTIVE Understand FUNCTIONAL COMPLEXITY Setup a REPEATABLE PROCESS to coordinate between business and IT CREATE VALUE for both This makes a BUSINESS ANALYST an important part of retail industry

13 SO WHERE DO I (THE BA) FIT IN? REALLY DEPENDS ON : a. What skill sets I bring b. What interests do I have c. What skills I am capable of developing d. What support does my company give me to develop my skills The proportion of business acumen, domain knowledge and technical expertise required by BA varies, depending on : Which force BA is addressing Which workstream BA is working in WORK STREAM BA SKILLS REQUIRED (Eg) Ability to BRING OUT THE STRUCTURE to define business problem and/or opportunity Leverage data patterns, statistics and find solutions that address business need Identify the impact of problem on business area top line, bottom line, customer, employee Ability to DEFINE AND REFINE clear and concise statement of the problem Stating the desired end state. Interviewing techniques, per principles laid out in the BABOK guide Client-specific processes and stakeholder mapping Define DATA MODELING OPTIONS available Choose / create a model that can be used for the specific business problem Analyze trade-offs (what is the accuracy? Possible model failure rate?) IDENTIFY DATA SOURCES Comm off shelf apps, bespoke apps, unstructured social data Data sampling methods Data sanitization and standardization techniques Data proxies (what if actual data is not available?) Ability to VISUALIZE DATA in Excel (Knowledge of R or Python is a bonus Provide recommendations based on the output of the data model Implement recommendations and measure success

14 THE OPPORTUNITY & THE CHALLENGE There is DEMAND OF GOOD BUSINESS ANALYSTS IN ANALYTICS FOR RETAIL with right mix of business, domain & technical skill. No 1 individual can fit in all workstream OPPORTUNITY CHALLENGE There is VAST AREA OF KNOWLEDGE THAT IS CONSISTENTLY EVOLVING From industry trends to analytical skills to changing market dynamics to disruptions in technology

15 SO WHERE SHOULD I GO KEY TAKE-AWAYS FROM THIS DISCUSSION The straightforward answer is: Develop analytical skills. Some pointers to help: Learn business analytics Understand how analytics works, what tools are used, the difference between you and a data scientist, framing problems, refining problem statements, analytical models in use Learn data sources Which system is responsible for what for your retail org ERP, CRM, ecommerce. Which system sends what data to other system Develop passion for data A basic knowledge of statistics, visualization, make sense of data patterns Understand business processes Learn processes based on interest: Sales, Marketing, Service, Order fulfillment are basics. Niche ones: Assortment planning, Forecasting, Warehouse operations, pricing etc Understand tools Get hands on with Excel Pivots, Power Pivots, and if possible with R, Qlikview, Python Learn data analysis techniques using visualizations, slicing/ dicing

16 Questions & Answers

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