Top 5 Analytics Use Cases In Consumer Durables Industry

Trends that are leading to the rise of the consumer durables segment

According to Statista, the consumer goods industry added a value of more than $1.4tn in 2023, with electronic products and their components leading with $0.9tn. This rise can be attributed to these key trends-

• Rising disposable Income- The fact that people’s earnings have increased leading to an increase in disposable income.


• The digital explosion- Gen Z and Millennials are leaving a vast digital footprint. Moreover, they are more susceptible to marketing efforts on digital channels.

The rise of the consumer durable segment has attributed to the increase in the amount of data that businesses deal with. With increase in data generated, organization can either get overwhelmed by its vastness or they can strategically implement analytics & AI to reveal the hidden patterns and insights.

Though it must be noted that the analytics itself has evolved, it is no longer limited to identifying the most optimum shelf space that occupies the most visual periphery of a customer. Rather it can now answer complex queries like what will be the demand in the next quarter in a specific store for a specific product?

With that said, let’s explore top 5 use cases in which Analytics & AI is changing the game in consumer durables industry.

Efficient inventory management & Lean Supply chain

Real-time insights into SKUs and proactive supply chain management helps consumer durables companies identify an optimal inventory level. This will result in cost-reduction opportunities across the value chain. Since logistics costs roughly 6-20% of a country’s GDP, this makes up a significant chunk of the cost for any consumer goods manufacturer. Hence, comprehensive supply chain planning and analysis of the steps involved are key to making the most of this spending.

To enable this, supply chain control towers have been acting as central nervous systems to enable key decision making around everything logistics or supply chain related. This is why 72% of them have expressed that control tower capabilities will be crucial for customer-driven growth.

• Planning command center- Monitor and create demand forecast by analyzing historical sales data to predict future demand. This can be done through predictive analytics, factoring in demand-supply economics.


• Logistics Control Tower- Real-time visibility into your entire inbound and outbound logistics operations gives you Enhanced visibility, cost optimization insights, and route optimization opportunities.


• Warehouse Tower- Helps to gain a bird’s eye view of your entire warehouse in dynamic 3D visualization with storage layouts, inventory levels, and ongoing activities such as the dispatch of goods in real-time.


• Inventory Tower- Predict product shelf-lives, lead time, and cycle times from suppliers and analyze share-of-wallet for different products to determine the amount of inventory held.


• Material Management Tower- Identify the best suppliers through supplier management based on price, quality, and reliability. Moreover, you can proactively identify risks and create procurement strategies.


• Fulfilment Tower- With this you intelligently route orders to the most appropriate fulfillment center and optimize your last-mile delivery.

Hence, with Data Analytics Solutions  as a true decision support system in making sourcing decisions, you can reduce total delivery costs by evaluating and managing transportation profiles, outsourced partnerships, and delivery types. Also, the platform can increase productivity associated with accurate receiving, picking and shipping, labor utilization, and throughput velocity.

Marketing Analytics in Consumer Durables

Today, companies have customers' data, which they can leverage to view and evaluate- where the purchase will come from(omnichannel), what will be purchased (Product mix), and when they will purchase (predictive analytics). Never has this purchase profiling capability been so conceivable as today with the amount of information that these customers leave behind.

Companies can leverage this information to model (predict) the consumer affinity for any particular segment of their offerings. Once they have this information, the customers can be enticed with relevant offers either through email or promotional messages or in-store sales personnel to quickly close the loop.

• Sentiment analytics- Given the millennial’s propensity to update their social status and opinions with everything (from products they love to the advertisement that they didn’t like and why), it is a treasure trove to identify trends.

• Promotion Channel analytics- Insights on the channels that are working in favor of the consumer durables players basis which a highly prioritized advertisement and promotional spend strategy can be formulated, thereby improving returns from these campaigns.

Note: Pricing optimization, Trade promotion management, and Product mix & assortment optimization are categorized together under RGM or Revenue growth optimization. What is RGM? It is the different strategies that aim to maximize a company’s revenue and profitability.

Sales analytics in consumer durable

Sales analytics solutions can help decision-makers maintain visibility on primary, secondary & tertiary sales data. It can also help them identify any cross-sell or up-sell opportunities and potential target accounts amongst the customer base.

Sales analysis highlights what products are trending across different retail stores. Insights from this exercise can drive inventory and shelf space management decisions. The power of near real-time analytics allows more effective collaboration between sales, marketing, and supply chain management.

Businesses can also use commercial scorecards to track and evaluate the performance of their sales representatives, teams, or departments. Instead of simply reporting sales numbers, it uses analytics to provide a comprehensive idea of the contribution of each individual to the overall goal. It allows further insights into the different KPIs and helps you determine the areas where the representative is strong vs where they are weak. Does a representative excel at closing deals but struggle with prospecting? The scorecard highlights these areas, allowing you to tailor-make training and development programs.

With the emergence of predictive analytics, organizations are now equipped with a powerful weapon. Some of its transformative uses include:

• Sales forecasting- Predictive analytics incorporates factors such as demand changes, peak seasons, and trends to provide a more accurate prediction than traditional methods.


• Customer segmentation- Gone are the days when customer categorization was based solely on past purchases. Predictive analytics delves into demographic information, browsing behavior, and initial purchase patterns to group customers based on perceived value.


• Sales resource distribution- Based on the sales representative’s past performance, type of product, region, and external factors, predictive analytics can suggest resource allocation based on their future sales potential.

Financial Analysis For P&L Management And Reporting

With the help of analytics solutions, executive insights reports and dashboards can be created, showcasing the metrics across the whole array of processes and departments. With some simple drag-and-drop features, executives can play around with the data to add or remove parameters to create a balanced scorecard for their business operations.

It takes immense effort from the Financial Planning & Analysis (FP&A) team to collate all the details cautiously and present a holistic picture of the business health. With the application of financial analytics solutions, the teams will not only achieve efficiency but will also be able to reveal hidden truths to support the company’s goals.

A powerful analytics tool provides easy implementation of the analytics mentioned above along with multiple other features-

• It integrates all the information in one place, removes duplicity, and creates a true picture of the condition of the company’s financials.


• It can help identify trends & bottlenecks through scenario-based planning & budgeting to determine the effects on Profit & Loss (P&L), Accounts Receivable & Payable (AR/AP), and other important metrics resulting from various financial choices.


• It can enable a comprehensive lag-free financial report generation through a BI platform, decision-makers can get a multi-dimensional view of aggregated expenses across categories.


• With a single platform to view all the key performance indicators (KPIs) can help discover unseen patterns that have the potential for increased profits.

Workforce Optimisation & Skill Development

The human workforce is a very integral and key element of any organization. The information related to performance, compensation, leaves, and others is recorded in every organization. With HR analytics, this information can be put to use in driving strategic workforce-related initiatives to save costs.

Organizations are implementing HR analytics platforms to take care of all these functions-

• Monitor departmental turnover and cost-per-employee to optimize retention.


• Identify skill gaps, engagement levels, and diversity trends.


• Segment employees based on their performance to make informed training and development programs.


• Create equitable compensation plans based on performance.


• Uncover behavioral patterns through absenteeism and performance analysis.

Additional Data Analytics Processes in Consumer Durable Industry-

The product manufactured companies go through various stages before reaching to end customer. At each of these stages, a huge volume of information is extracted. This includes data from shipments (which tracks the journey from the manufacturer warehouse to a distributor or retailer), sales information (at retailer POS), consumer surveys (collected on the field and consisting of qualitative & quantitative data), and data when shopped online.

• Consumer Support- Consumer durables is an industry very close to customers because of the dependency on these products in everyday life. An analytics platform greatly helps in the timely resolution of customer tickets by flagging outstanding queries after it has crossed a certain threshold.


• Competitive Benchmarking- The data analytics solutions help consumer durable companies benchmark their performance with the market. It can reveal areas of improvement that would lead to enhanced category management practices to look at pricing, substitution, segmentation, and retailer/category performance.

Generative AI in the Consumer Durables Industry

Generative AI has reshaped the industry with its ability to automate tasks with a high degree of efficiency. McKinsey reported that it has the potential to automate 60-70% of all employees’ tasks. This provides additional resource optimization opportunities by freeing up employees for more strategic tasks. Let’s look into these tasks in the different use cases in the consumer durables industry.

Conclusion

In light of dramatic changes in the consumer landscape, it has become imperative to track and predict customer behavior more than ever before. Being able to gauge that with the help of the information they leave behind, creates an insurmountable advantage.

An analytics system can pinpoint areas of concern like product defect ratio, demand & supply pull, and much more, allowing stakeholders to make winning decisions. It helps in the efficient management of raw materials sourcing and quality, optimizing inventory, and understanding margins over costs.

Moreover, Generative AI has opened up new avenues of automation and creativity which can help enhance design, optimize processes, and personalize customer experiences. If there is a better time to embrace Generative AI, it is now. Businesses should position themselves in the forefront of AI-related transformation if they plan to stay relevant in the future.