Customer Story

Packaging Manufacturer Streamlines Data Integration after Acquisitions to Accelerate Company Growth

What we did

  • Data strategy roadmap provides packaging manufacturer recommendations on the people, processes, and technology they need to integrate and analyze the data accumulated from multiple company acquisitions.
  • New data architecture will allow the business to improve the onboarding process of new acquisitions and accelerate the rate of additional growth.
  • Modern BI tool—Qlik SaaS—will provide consistent analytics across all lines of business with key KPIs, allowing the company to scale and improve relationships with suppliers and vendors.

Industry

  • Manufacturing

Technologies

  • Azure
  • ·
  • Databricks
  • ·
  • Qlik
  • ·
  • Snowflake

Goal

The packaging manufacturer has acquired several companies in the last few years and doesn’t have plans to slow down any time soon. One of their main goals is to quickly and efficiently onboard the companies they have acquired and integrate and make use of all the data they have amassed along with these acquisitions.

Problem

To continue down their aggressive growth path, the manufacturer looks to speed up the rate they can onboard new companies and increase visibility into operations across all businesses. To do this, they need to:

  • Streamline and automate their onboarding process so that they can efficiently integrate data from their acquired companies, as well as analyze technical debt and make changes where necessary.
  • Better understand the key, basic metrics—headcount, costs, and production efficiency—from all the acquired companies and provide more accurate and automated corporate reporting to stakeholders and investors.

The faster that they can onboard new acquisitions and gain insights around how they are performing, the faster they can scale and realize the value from the acquisitions.

Solution

We conducted a strategic data assessment of the company’s different sub industries and created an inventory of data sources, diagramed the current state flow of data, and documented data requirements for each business. Next, we identified use cases in key areas—inventory, freight and logistics, spend, and sales—spanning all lines of business and documented the steps to achieve these use cases, including the collection and integration of critical data.

We determined where the manufacturer was on the data and analytics maturity scale and identified key areas required to make progress toward the next level of maturity. Understanding and being able to communicate to others in the organization where they are today, will help them get the buy-in required to make progress.

A modern data architecture accounts for the entire data lifecycle.

Our technology and architecture recommendations included:

  • Azure Synapse for cloud storage, Azure Data Factory and Azure Data Lake for their data storage, integration, and transformation needs, and Databricks for future machine learning use cases.
  • A transition from QlikView on-premises to Qlik Sense SaaS for ad hoc analysis needs—including inventory planning, spend on raw materials, freight and logistics, and sales analysis. The company is a long-time user of Qlik, and the tool is a good fit because it will allow them to move quickly in retrofitting imperfect data that comes in with new acquisitions.
  • As the company continues to grow through additional acquisition, we outlined an option of headless BI—a way to break free from the constraints of one analytics tool. Instead of certain departments inevitably going rouge with their own BI tool, we suggested a framework to define the parameters in which new tools could be added.

The Results

With the data strategy roadmap and recommendations that we outlined in the assessment, the packaging manufacturer can make informed decisions on how to upgrade their data and analytics ecosystem. They were equipped with a comprehensive evaluation of the various components they would require to successfully scale to sustainably handle expected growth and to proceed strategically to increase data and analytics maturity.

This included not just recommendations around technology and architecture but also recommendations on people and processes. They were able to not only understand the technical debt of each recommendation, but also how it would benefit the organization in the long run and how this would affect the suggested priority and placement on the strategy roadmap.

Once the business implements the new data architecture, they can begin to:

  • Accelerate and enhance the onboarding process, gain valuable insights about performance, and make informed decisions about future growth plans. This will greatly increase the amount and type of information they can consolidate from the acquisitions and reduce the risk of making a bad decision.
  • Identify ways to reduce costs, improve processes, and meet sustainability goals across the business with better corporate reporting.
  • Provide consistent analytics across all lines of business with key KPIs, allowing the company to scale and improve relationships with suppliers and vendors.

This is one of the largest manufacturers of paperboard and sustainable paper-based packaging for some of the world’s most recognized brands of food, beverage, foodservice, household, personal care, and pet care products including Kraft Foods, Anheuser-Busch, General Mills, and Coca-Cola. They have more than 24,000 employees throughout more than 130 facilities.

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