3 Data Driven Challenges in Consumer Packaged Goods Companies

As one of the biggest drivers of change and innovation, the Consumer Packaged Goods (CPG) companies have always launched innovative products to meet a bolstering array of human wants. This rapid growth was made achievable and profitable only because of continuous product innovation. However, the past is no guide to the future.
According to Nielsen (NLSN) report, 2016, “only 15 percent of newly introduced consumer packaged goods succeed in the market.” Because the consumers are increasing finding the digital medium— e-commerce, Omni-channel retailing, and mobile platforms more compelling than the traditional stores. And, with this eruption there is a need for intelligent innovation in CPG industry.
Also, with this transition comes the enormous amount of ‘Big Data’, which can be used to drive business decisions, and can also help create a compelling and integrated view of the consumer experience. But doing so is not as easy it seems. Before turning any type of data into valuable insights, the CPG industry needs to address the following barriers:

Getting the right data

CPG companies today have abundant data, sourced internally and externally. But this doesn’t guarantee a great value to enterprises’ sales information. Since data obtained for entities may be incomplete or can be in an incorrect format, the quality of data is questionable.
So, when enterprises crawl in to gain a timely visibility into their sales information, it leads them to faulty conclusion. Data-driven decisions are only as good as the quality of data you collect. Using data to drive business decisions requires the right data collection system that can transform these data into actionable insights.

Gaining the proficiency to use data

Having more data doesn’t necessarily lead to actionable insights, and the best analytics tools can often fail to identify business objective.
CPG enterprises often assimilate data from different external sources (subsidiaries, channel partners or data aggregators), which inherently brings the issue around data contextualization.
For instance:

• Altered product identification from original manufacturer designated IDs
• Products attributed to different classifications across different value chain partners
• Product information in a different language

Without data contextualization CPG companies won’t be able to derive meaningful insights in real time.
According to Nielsen, “Harmonization is an ongoing process that requires strict governance and constant monitoring.” But when the process isn’t in its place and is unable to draw from both local knowledge and global expertise, it delivers inaccurate information.

Deriving actionable insights from the harmonized data

The spiral of innovation in the digital era hasn’t been kind to the CPG companies. To top the already existing sales, promotional, supply-chain, and finance data; social media is a new entrant to add to the woes. And what becomes critical for CPG organizations now is how to manage, streamline sort, filter and make sense of these data mountains; making them easily graspable and insightful in real time.
As most CPG companies expand their foothold in developing markets they unlock new opportunities, and the challenge to capture critical downstream data in the distribution channel.