CPG Companies Need “Better” Before “New” When it Comes to Promoting Growth

Topics: Insider, Optimization, Predictive Analytics

Terry Ziegler, CEO and co-Founder T-Pro Solutions

When thinking of the powerhouse CPG companies (P&G, Nestle, Kellogg’s, etc.), it is rare that the conversation revolves around vulnerability. However, in the Tech Crunch guest post, “Large CPGs are under attack by startups… and consumers are winning” by Zuora CEO Tien Tzuo, the premise that these foundational companies need to make improvements to remain at the top of the industry comes to light.

Mr. Tzuo correctly points out several strategies (social, e-commerce, subscription models, etc.) that can position these companies to see the similar growth and success as their smaller and often more competitors.

However, underlying the implementation of new initiatives is an analytical blind spot of historical inefficiency and lost opportunity in the area of trade numbers-money-calculating-calculation-large.png
promotions. Trade promotions and trade marketing represent for a large portion of a Consumer Goods company’s in-store marketing and account for an estimated 23% annual investment. This is a $200 Billion annually spent in the U.S. alone.

The inherent problem with this investment is that while these programs bring in large amounts of data Consumer Goods companies struggle to cleanse, integrate and apply this data to a measurable picture of the promotional performance. When they do, this process is largely manual, error prone and spreadsheet dependent leading to inaccurate understanding and poor decisions. Despite these concerns, the Promotion Optimization Institute states, “We still see a large number of activities that are done in spreadsheets instead of through a system”

So while initiatives driven to expand the capabilities of Consumer Goods companies are important, companies must consider how to gain control of their current investments to increase informed decision making leading to sustainable revenue growth.

 

Trade promotions and trade marketing represent for a large portion of a Consumer Goods company’s in-store marketing and account for an estimated 23% annual investment. This is a $200 Billion annually spent in the U.S. alone.

 

For large and small companies alike, adopting an analytics mindset to managing trade promotion brings both added insight and agility to this revenue management approach in 3 areas:

Data accuracy – Ernst and Young, in their publication “Can your portfolio of brands provide the answers you need? Five questions consumer products companies should consider to optimize their portfolios” asserts that 46% of CPG companies find access to accurate and comprehensive data a challenge.  To get a full picture of promotional performance, companies need to bring together the data sets that affect promotions effectiveness – POS, spending and shipment. Unlike many current measurements of promotional success, integration of these data pieces paints a more holistic picture of promotions performance eliminating potential inflation. Similarly, removing the manual component from this process eliminates errors and saves organizations time compiling siloed data and allows for more time for event and plan analysis.

Quantifying performance – It is one thing to have the data and another to use it. With analytics Consumer Goods manufacturers can measure the ROI and KPIs of promotions. This means that finally organizations have a timely, measurable indicator of how promotions are contributing to overall growth. The McKinsey & Co. report, “Winning in consumer packaged goods through data and analytics” asserts that successful CPG companies are different in that, “They track a comprehensive set of key performance indicators and conduct formal reviews, paying special attention to deviations from trade-investment guidelines and imposing more stringent consequences for overspending (such as withholding incentive pay from field reps or canceling planned events with the retailer).” This insight means that companies can quickly make adjustments to compensate for poor performance, resource realignment or market variation.

Predictive planning and optimization – The application of predictive analytics to quantified promotional analysis brings life to future planning. No longer are companies tied to guessing what works best or simply repeating past plans. Instead companies can directly tie future planning to company revenue initiatives by predicting the outcomes of promotional events and plans. Couple this with a prescriptive optimization capability and the solution will use constraint-base models to run through the event or promotional mix possibilities to determine the optimal plan to meet a company’s goals.

 

The inherent problem with this investment is that while these programs bring in large amounts of data Consumer Goods companies struggle to cleanse, integrate and apply this data to a measurable picture of the promotional performance.

 

With this in mind, Mr. Tzuo’s conclusion that “Consumers have changed — and the consumer packaged goods industry needs to respond” is accurate, but addressing this starts with better practices and better understanding to get to better results. While this applies to CPG companies of all sizes, the fact of the matter is that large companies are managing more data, more categories, and more customers. However, the size of a company should not mean lower expectations or missed opportunity. A properly supported and aligned analytics initiative can provide the foundation to close the growth-rate gap between large and small companies and more importantly create a sustainable and adaptable revenue model for future growth.

Next Steps: Download our e-book How to Optimize Your Trade Promotions


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