Click to learn more about author Devansh Sharma.
As the world is slowly and gradually recuperating from the pandemic, markets
are opening, businesses are restarting, and customers are returning, but the
new normal is still full of uncertainty.
What It Means for
Demand and production have contracted across sectors; for some, it has
contracted to as high as 8 to 10 percent from pre-pandemic levels.
This snapshot of a McKinsey & Company report on the impacts of COVID-19 on advanced industries clearly reflects this drop in demand.
This is not new, as every black swan event is followed by pessimism across markets. Customers become cost-conscious, demand slows down, and boardrooms are filled with questions of sustainability. Such adverse scenarios require a transformational approach to strategy. Stalwarts cannot traverse these times based on their past glory. They need to think fast, apply faster, and correct course at lightning speed.
Each company should take a closer look at their pricing strategy to
navigate these challenging times. Organizations need to go granular and have a
clear view of pricing data coming from the SKU level. Some of the big players
have already started doing this, but most industries, by and large, are still
stuck in their orthodox ways.
Now is the time to get the adoption of analytics discussion out of the
boardroom and let data and insight help us sail through this uncertain period.
What Measures Can Help Organizations Navigate Through the New Normal
Data Integration: Data in silos is a
longstanding challenge of the industry, but in current times, this needs our undivided
attention. Insights from the data are seen as the panacea for the current
problem of a demand slowdown. The more we collate and harmonize data, the
better our forecasts and predictions will be, which will further help in faster
decisions. There are organizations that have been capturing data for many decades
now, but they lack the system to drive insights from it.
Harmonizing data is easier said than done. It is a massive effort for
organizations, as data runs in TBs to PBs in some cases; to get it all at one
place is a gargantuan task. It should be done in at least two phases. In the
first phase, organizations need to integrate data from important data sources,
which could help in dynamic pricing and demand and production forecasts. In the
second phase, they need to carry out a similar activity over other data sources
like HR, finance, administration, etc.
Identifying Trends: Once the data is harmonized, data and analytics teams need to focus on identifying trends in pricing and demands for the products at the SKU level. They should try to achieve as much granularity as possible in this activity, including the following:
- Segment the Products: Uncertain times (such
as today) require a granular approach to business. Organizations need to go beyond
their high-level approach based on product mix, product portfolio, and standard
pricing. These times warrant a more granular look at product portfolios to
identify opportunities to maintain or grow revenues.
Organizations need to benchmark each product on a pricing power vs. competition matrix and look for the products in each market where they command the pricing power, as these will be winning products for them.
- Segment the Customer Base: Segmentation is a powerful
technique. It could be used not only to find out the winning product but also
to know more about the customer. Organizations need to segment the customer
base on the basis of specific attributes such as value drivers (for instance,
speed of delivery), relationship type, industry, etc. — and look forward to the
winning customer segments. The answer to improved revenue lies in the amalgamation
of winning customer segmentation and winning products.
Pricing Analytics/Product and Region-Based Pricing: With identified pockets
of opportunities, marketing and analytics teams need to work hand-in-hand to
create a compelling value proposition of winning products for the identified
For example, Auto OEMs (manufacturing bearings, lights, and axles) could
segment the customer base into two-wheeler and four-wheeler producing customers.
The demand from the two-wheeler segment has already reached pre-pandemic levels
and is growing at a faster pace than the demand from the four-wheeler segment.
If the OEM uses our pricing power vs. competitor dominance framework,
it could identify the opportunity pockets and can ramp up production for the
two-wheeler segment and also redefine pricing.
Real-Time Tracking: The job is not done
yet. One clear differentiator in these times is the response time of
organizations; dynamism is the key to survive and flourish in these times. With
the social media revolution that has unfolded in the last decade, consumers are
quick in responding to the introduced changes. Organizations need to keep pace
with it and develop a robust mechanism to collect and analyze broad sets of
external data sources — such as web traffic patterns, daily retail panel data, and
online prices, and incorporate all of this into the pricing model, which would
further help in building a moat around pricing.
Organizations are traversing through untraveled territory in this
pandemic and are witnessing subtle changes in customer behavior and demand
patterns along the way. These changes started as subtle clues but will evolve
into long-term patterns. Organizations need to pick up these subtle clues and develop
robust mechanisms that could become their moats in the long run and could widen
the gap with their nearest competitors.
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