The 13 Scariest Things About Using Bad Retail Data for Decision-Making
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Using bad data for advanced analytics, actionable insights, and decision-making is enough to make consumer goods companies and retailers scream.
It can have numerous, horrific consequences, and while it's challenging to rank them definitively, the following are some of the scariest aspects of relying on flawed POS and inventory data—and weekly or monthly demand and supply data—for critical decision-making:
- Misinformed Decisions: Bad, dirty retail data can lead to incorrect conclusions and poor decision-making by many CPG teams, including sales, marketing, supply chain, and finance. These decisions can potentially result in spine-chilling financial, operational, or strategic consequences that would make you want to run to your mummy.
- Financial Losses: Making important business decisions based on inaccurate or incomplete data, such as syndicated data, can lead to ghastly financial losses, as investments, resource allocations, and pricing strategies may be misguided—taking your sales and profits straight to the grave.
- Reputational Damage: Flawed retail data can lead to deadly errors in demand planning and forecasting, out-of-stocks or overstocks, and poor retail execution, putting a major hex on your company's brand reputation.
- Loss of Trust: Consumers, retailers, and even employees can lose trust in your organization and brand—and possibly ghost you and your products—if they discover that you've been making decisions based on unreliable data.
- Compliance and Legal Issues: Using bad data may result in violations of regulations or legal requirements, leading to penalties, lawsuits, or regulatory actions that could haunt your company for longer than you might think.
- Wasted Resources: Acting on inaccurate data can lead to wasted time, money, and various resources, as you may need to correct errors and re-evaluate your strategies to keep you from going batty.
- Inefficient Operations: Bad data can result in inefficiencies in your new product launches, trade promotions, retail replenishment, supply chain, and resource management, leading to terrifying higher costs and lower productivity that would certainly spook your finance department.
- Competitive Disadvantage: Using unreliable point-of-sale and inventory data puts your organization at a monstrous disadvantage compared to sinister competitors who make data-driven decisions correctly.
- Missed Opportunities: Bad data can leave you alone in the dark, causing brands to overlook potential opportunities for growth, innovation, or market expansion.
- Poor Customer Experiences: Accurate consumer data is crucial for personalization and improving the shopper experience. Bad data can put a dreadful spell on accurate customer profiles and interactions.
- Employee Morale and Retention: Decision-making based on bad data can create a frustrating and demotivating work environment, potentially leading to some wicked, high turnover.
- Difficulty in Root Cause Analysis: When problems arise, seep, and creep in, identifying and addressing the underlying issues can be frightful and challenging with unreliable data, making it harder to prevent future incidents.
- Bias and Discrimination: Bad data can perpetuate distressing biases and abominable discriminatory practices, as decisions made on inaccurate information may be influenced by existing prejudices in the data.
No need to fear or panic—your strategic decision-making doesn’t have to be cursed forever. If you prioritize retail data quality, establish data governance processes, and invest in automated, cloud-based retail data collection, validation, and harmonization solutions, such as Retail Velocity's VELOCITY® data platform, you can mitigate these hair-raising risks and make more fang-tastic informed decisions that can help you bury the competition and grow your business spooktacularly.
Don’t let bad POS and inventory data give you nightmares. Get in touch with us today and we can discuss some bewitching ways you can gather and leverage the most accurate and reliable retail data.