Jun 09, 2021 | 2 Minutes Read

What are the Top Challenges and Fixes to Incorporating Cloud Computing for CPG?

BannerImage

Cloud computing has transformed the capabilities of CPG companies, helping them engage consumers digitally and enhancing omnichannel consumer experience capabilities, providing insights on customer journey and enabling them to delve deeper into customer trends and preferences. Additionally, it has also helped them improve their existing digital ecosystems and to make the most of their analytics infrastructure. In fact, a Gartner study forecasted that worldwide end-user spending on public cloud services would grow "18.4% in 2021 to total $304.9 billion, up from $257.5 billion in 2020.” [1]

As CPG companies set out to implement cloud computing for their organizations to improve customer experience and enhance operational capabilities, here’s an overview of the difficulties that they are likely to encounter and the respective fixes that can help resolve the challenges:

1. Data Collation & Data Standardization

CPG companies are most often excessively dependent on retailers for data pertaining to sales and customer product perception. Most other industries have direct access to first-party consumer data and it is difficult for CPG companies to collate equally rich direct-from-consumer data. Furthermore, with multiple retailers pushing out sales online, they also have access to insightful e-commerce sales data to discern more characteristics about consumer behavior. This only widens the information and data collation gap for CPG companies.

Adjacent-industry brands that directly interact with consumers are also tough competitors for CPG industries – this is because of the former’s DTC setup which gives them access to first-party data. For example, a legacy CPG brand for sanitary products is going to face shortage of first-party data when compared to a private, DTC CPG brand that offers personalized, customizable products. Therefore, the lack of PoS data is a huge challenge for CPG companies when they try to create efficient cloud computing systems.

In this regard, investing in first-party data is necessary to maintain a competitive edge. CPG companies can tie up with retailers who are willing to share PoS data. But given that not all retailers would be willing to share this information, CPG companies must be ready to create PoS interactions with customers. Traditionally, CPG companies have been working on the same via surveys, questionnaires, etc. But these are challenging to scale. Alternatively, vying for researched data from third party sources can prove expensive.

CPG companies must instead aim to interact with their consumers via online channels. While they might not immediately gain PoS data like e-commerce retailers, they can instead engage in customer interactions through their social media channels, mobile applications, website interactions, and interact with the consumers wherever and whenever possible during the course of the customer journey. By channeling efforts towards directly discerning customer preferences and can prove to be extremely insightful first-party data. This can also help CPG brands bolster customer relations and understand brand perception.

2. Fragmented Usage and Adoption

Most often companies that are venturing into cloud computing might not have a pre-existing streamlined cloud computing system in place. Most teams often take up integration ad-hoc without a centre of excellence that takes up responsibility for cloud computing. Especially with multi-national CPG companies, transition to cloud computing is not taken up at a global scale but rather at a fragmented local level, leading to lack of accountability and difficulty in facilitation of cross learnings. The lack of one unified governance team also implies friction and lack of standardization when it comes to data templatization, data governance, DQM, etc.

Teams could instead pilot the cloud computing in one centre, set up practices and data governance policies to be followed org-wide, and ensure efficient DQM. The pilot could then further be introduced as a success story to fuel further evangelization. Once these processes are setup, they can then be automated for continuous testing, assurance of compliance with governance policies, issue alerts for any out-of-the-ordinary activity on the cloud, and help efficiently scale cloud computing efforts, across all branches of the firm.

3. Migration

Most companies have digitized their processes and have a pre-existing cloud ecosystem/architecture. Moving these pre-existing systems and applications can prove to be extremely challenging. About 92% enterprises have a multi-cloud strategy; 82% have a hybrid cloud strategy," but organizations are estimated to "waste 30% of cloud spend." [2]

If the team has not accurately planned their budget to facilitate a streamlined move to the cloud they are likely to struggle at multiple points of their cloud migration with issues like inefficient or long drawn migrations. Inefficient move to the cloud also results in security issues and might necessitate frequent trouble shooting and reduce overall working efficiency.

Conclusion

Digital transformation that was already underway has been accelerated with the necessitation of work-from-home setups because of pandemic disruption. It is fitting that a Gartner study predicted in November 2020, “70% of organizations using cloud services today plan to increase their cloud spending in the wake of the disruption caused by COVID-19.”

To stay ahead of competition and provide premier products and services to consumers, companies must invest responsibly towards bolstering their digital capabilities and cloud computing would need a significant chunk of this budgeting. CPG Companies must draft out an extensive plan, preempt challenges to implementation and advise on fixes to seamlessly utilize the benefits of cloud computing.

AUTHOR BIO

Sreeharsha Naik | Associate Principal

Sreeharsha has over a decade's experience in databases, data warehousing, data engineering, product development and data science in the AI/ML world. He is keen in making sure that the enterprise architecture being built is scalable & tool/cloud agnostic. He is an avid stock trader and spends most of his time off-work into options & equity trading analyzing indicators, candle sticks and more.

share article

facebook linkdin twitter

Want critical data insights to unlock business value?

Get Started
mobilelogo
Linkedin Instagram Facebook Twitter
Cookies policy Privacy policy