TPx and RGM are data hungry solutions and our CPGvision platform is certainly no exception. Poor data quality can hinder successful implementation and managing change and lead to low user adoption or worse - bad decision making. However, investing in high-quality, consistent, and well-organized data can yield great returns.
Data can either help or hinder progress. To avoid the issue of poor output from poor input (garbage in, garbage out), it's crucial to focus on good data quality. There isn't an easy, one-click solution, but investing time and resources in building a reliable base of quality data pays off. A clear data strategy benefits the whole organization.
Why CPG organizations need a data strategy
To combat silos
In today's complex buyer landscape, keeping data isolated in different departments prevents a complete understanding of consumer and customer behavior. Departments must work together to grasp consumer issues, motives, and habits for better marketing and sales. If, for example, sales controls trade data and market research keeps consumer insights separate, the company misses out on the synergies of integrating these insights.
For security
Data is a crucial asset for any company, and protecting it is essential. It's important to have a secure platform where everyone can access data safely, without risking security breaches. Sending data through emails in spreadsheets is both common and risky. But what alternative have we given employees who need to run the business? More often the answer is none, so risky behavior proliferates.
For decision-making
Data-driven decision making is about using insights to influence important business decisions, and when it comes to the sheer size of trade budgets, there is no better use of data-driven decision making. Successful companies rely on data to make decisions. Without this, they risk missing growth opportunities or making expensive errors.
Transitioning from intuitive to data-driven decision-making is more objective and enables agility and preemptive strategies. It allows for post-decision evaluation, increasing organizational accountability. However, this approach requires the capability to analyze and act on data from multiple sources. It involves compiling this data to enable both prescriptive and predictive analytics.
Data means competitive intelligence
“Competitive intelligence programs uncover and analyze market and competitor activity to provide actionable intelligence. Ultimately, the goal is to provide leadership with useful insights to support more informed business decisions.” - Forbes
Using data effectively gives businesses a competitive edge. Companies that know their market and competitors well can create strategies that keep them ahead. It's important to constantly analyze past events and spot new trends to maintain this advantage. Overlaying artificial intelligence to predict a competitor’s next actions is the next frontier of competitive intelligence. Again, the proper foundation of data is the enabler.
Data allows for quicker, more accurate decision-making
A good data strategy helps an organization shift from just gathering and assembling data to analyzing and acting upon it.
Who benefits:
- Finance
- Sales
- Marketing
- Revenue Management
- Supply Chain
Roadmap for building your data foundations: Define program goals
Examples include developing data-driven processes, boosting revenue by identifying opportunities through data, making data more user-friendly, and fostering a culture of making decisions based on data. Prioritizing security and compliance is also crucial.
How to assess your company's current state
Conduct an audit and inventory of all data within the organization, including data created internally and obtained from third parties. Record who manages each data source, its users, and evaluate its quality.
Look for ways to streamline and reduce duplication. Find any significant data gaps blocking crucial business results. Discuss with key stakeholders their objectives that need sophisticated data solutions and their main obstacles in meeting these objectives.
Finally, create a plan for obtaining data needed to fill knowledge gaps.
1. Cleanse
The audit will help you find chances to clean up the data. This might need substantial and targeted efforts in some organizations. Data cleansing typically includes removing duplicate records, updating outdated information, filling gaps in incomplete data sets, and the most challenging task - identifying and removing inaccurate data.
2. Harmonize
Harmonize data sources whenever possible; the effort pays off. Combining different data sources brings significant advantages. Ensure systems that should communicate with each other are integrated. This allows smooth data flow, reduces manual data gathering and downloading, and improves data security. For example, when creating baselines in trade promotion management, we rely heavily on point of sale data collected by syndicated data companies. But this only tells a part of the picture. Harmonizing other sources, like macroeconomic data, online activity, etc., gives us a different and more complete projection.
3. Governance
Ongoing data governance is about establishing, monitoring, and enforcing data policies. Atlan provides a good checklist of the components of data governance, which should include:
- Outlining objectives
- Defining roles and responsibilities
- Establishing policies and procedures around privacy, security and acceptable use of data
- Managing data quality
- Establishing a data steward responsible for keeping everything up to date
- Training on policies and best practices
- Measuring performance
- Developing a continuous improvement program
4. Centralize and systemize
Ensure that those who need data access can get it. Set up a robust data platform that supports a flexible system environment. This lets business leaders use the most effective tools for their needs without compromising functionality to align with the broader IT framework.
Harness the power of data-driven strategies with CPGvision
Data-driven decision-making is crucial for businesses to seize growth opportunities and secure a competitive edge. It involves more than just collecting data; it's essential to govern data policies effectively and centralize data access in a system that is both flexible and functional for your business needs.
Discover how CPGvision can support data harmonization and foster data-driven decision-making, crucial for establishing a data-driven culture. Our complete suite of solutions, fueled by harmonized data and AI-powered predictive analytics, enhances trade spending, price management, financial planning, and forecasting for better outcomes.
Don't let data challenges slow you down. Click here to explore our solutions and transform your data into your most powerful asset today!