That pretty much describes the initial reaction of most people to the pandemic and its immediate fallouts. They made a beeline to stock up on essentials, struggled with getting a remote work setup ready, were forced to play it by the ear, and had to deal with uncertainty by making important decisions based on probabilities.
But, it’s not just the people who panicked. Turns out, a lot of manufacturing businesses were caught off-guard and didn’t quite know what’s required for maintaining business continuity in uncertain times. For instance, some scurried to stock up on protective equipment and sanitisers while neglecting supply chain disruptions.
And the ones who did take cognisance of the latter failed to anticipate the pandemic’s effect on consumer demand and buying patterns. However, those who did prepare for supply chain and consumer demand issues found a completely unexpected problem knocking on their doors – surging warranty claims driven by COVID-19.
Data – Best Antidote to Emotion
Panic is an emotion and since it’s people that helm any business (manufacturing or otherwise), it’s unfair to expect them to maintain zen-like calm in choppy waters. This emotion-driven decision making is what played out with manufacturing businesses at the pandemic’s beginning, resulting in bias and blind spots.
Pressed with the need to churn out products during the pandemic, many manufacturers focused excessively on worst-case scenarios (ala, recency bias) while being oblivious to more practical concerns (ala, blind spots).
It’s this gap in cognitive functioning that can be addressed by data or more accurately, deploying analytics in manufacturing.
Data analytics and business intelligence help you to make better decisions by identifying threats, quantifying them, and finding the most optimum solution to a specific problem.
If you’re part of a manufacturing business, read on to know how analytics can help you to not just cushion the impact of this pandemic and future disruptions but also make a sizable and immediate difference to your bottom line.
How Manufacturers Can Use Data Analytics
- Demand and Sales Forecasting
Traditionally, demand forecasting has helped manufacturing businesses plan their production using a mix of historical data and gut-based decisions. However, the fluidity of the pandemic-induced lockdown meant the traditional forecasting methods weren’t able to cope with changes in demand and consumer behaviour.
This showed in the way several consumer and industrial products kept going out of stock despite good demand. The changed consumer behaviour also provided a fillip to new product categories (masts, sanitizers, laptops), lower-priced options for popular brands/products, and demand from new geographical areas due to work from home.
A data analytics solution can help you deal with such sudden shifts by collecting data on and analysing your customers’ decision-making process. For instance, what do they buy, when do they buy, how do they buy (pick-up from the store or home delivery), how do they pay etc. are all useful data points to create a demand forecasting model.
Such a model not will not only be more accurate than intuition-driven decisions but will also be better and faster at identifying and quantifying changes in consumer behaviour.
In fact, you can hire dedicated developer to improve this accuracy further by using multiple online as well as offline data signals to map your customers’ journey and refreshing the data models at shorter, frequent intervals.
- Inventory and Logistics Planning
COVID-19 has hit many manufacturing companies where it hurts most, inventory and logistics planning. There are stories galore of businesses struggling because of operational and financial problems of their vendors/suppliers, supply chain inefficiencies brought on by unreliable forecasting due to demand volatility, and lack of real-time data on supply chain bottlenecks caused by localised lockdowns and restrictions.
This is where analytics-driven inventory optimization can help manufacturers get a holistic view of their raw material stocks and expected supply shocks. For instance, such a system classifies the inventory on the basis of stock type in the manufacturing plant and its trends.
The solution can further identify and classify areas of this inventory that are slow-moving, non-moving, or deadstock, thus helping you cut costs and optimize your cash flows.
Similarly, an analytics solution’s real-time reporting feature keeps track of your input and output in real-time, helping you assess price points, changes in lead time, and supplier partnerships.
Such inventory data can be combined with telemetry data from your transportation machines and vehicles to give you real-time, precise, and actionable insights into your logistics planning.
- Spend Analysis
The largest chunk of a manufacturing company’s external spend goes towards suppliers and vendors. By bringing this cash outflow under the data analytics lens, manufacturers can optimise their procurement cycle and supplier management.
Spend analysis using analytics can also help with sourcing vital raw materials from locations with lower operational restrictions. This will help your procurement department reduce costs, manage risks more effectively, and improve the company’s cash flow.
During situations such as this pandemic, it’s important to know where and how valuable cash is spent, so that avenues to save can be identified.
Not only does spend analysis help with this but also chips in with reducing supply chain disruptions, creating an agile supply chain to deal with fluctuating demand, and minimizing price impact due to commodity market volatility.
- Financial Health Planning
A business should prioritise its financial health over everything else during a Black Swan event such as COVID-19 as it’s the only way a company can bridge gaps in cash flow, remain solvent in the long-term, and deal with uncertainties.
This holds truer for manufacturing businesses where business continuity is harder to maintain in the face of crises.
Advanced data analytics and business intelligence can help your business with liquidity planning by tracking operational bottlenecks, vendor supplies, and customer demand. Similarly, it can also help you plan for different scenarios by creating responsive budget estimates.
A sound financial plan based on data analytics, in this way, lets you plan for evolving budget requirements by accurately estimating the impact of internal as well as external drivers on your business plan.
- Workforce Engagement
While automation in manufacturing is growing by leaps and bounds, the need for a workforce equipped with the required digital skills to handle complex machinery and process has never been greater. Incidentally, this applies to both blue-collar and white-collar jobs.
Data analytics can help manufacturing companies reskill their employees in digital and analytical skills, which will help them solve problems using real-time operational insights. Moreover, analytics has helped manufacturers ensure production continuity with effective health-risk management through contact tracing, demand-to-availability matching, and high workforce utilization.
Over to You
While the world is returning to normalcy as the pandemic subsides, it cannot be business as usual for manufacturing companies that relied on intuitive decision-making. The decidedly un-glorious uncertainties in modern manufacturing are amplified by events like COVID-19, making data the most reliable source to base your business decisions upon.
As an analytics-focused custom web application development company, we can help your company become more efficient and productive, which are the surest ways to increase your profitability in the long run.
To know how you can leverage data for greater success during and after the pandemic, get in touch with our BI consultant now.
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