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Algol Chemicals

Human-centered discovery to support a chemical distributor’s growth

People in an office

When a century-old chemical distributor sets its sights on an ambitious growth strategy, the foundations need to be rock solid. Algol Chemicals partnered with Reaktor to do a deep dive into their internal operations to find the most high-leverage areas of improvement. In close collaboration with their teams and senior management, we conducted a comprehensive discovery process within their sales and customer success workflows. This allowed us to identify the most valuable opportunities to tackle and lay the groundwork for their next chapter.

Project highlights

70+ identified areas of improvement

A deep dive into sales and customer success operations allowed us to find the most high-leverage opportunities for improvement.

An actionable roadmap

Focused on the highest-impact initiatives with the best chances of implementation success.

Concrete AI opportunities

Mapped development areas to AI-based solution opportunities.

Tight collaboration

Working with teams and senior management helped create a 360 view of workflows and find better solutions.

Background

Founded in 1894, Algol Chemicals has built its reputation as a trusted provider of chemical raw materials across the Nordics, Baltic countries, Ukraine, and India. With an ambitious growth strategy in place, the company recognized that their internal operations needed to evolve to support their expansion plans. The focus was to make sure that their sales and customer success functions could scale efficiently without compromising the quality.

A deep dive into the day-to-day

At Reaktor, we strongly believe that the best insights come from users and customers. And that’s why we like to start with discovery. We began by interviewing stakeholders across different departments to gather a comprehensive understanding of the company. Every area or topic we looked at, we did so from the business, user, and technical points of view.

Throughout the discovery phase, we worked closely together with Algol’s teams to understand how different stakeholders understood the expected workflows. In addition to interviews, we ran workshops and mapped both official processes and what we gathered the actual workflows to look like at the end of the day. In other words, how managers imagined an official process to be conducted versus how the teams experienced it in reality. Doing this work revealed important insights when it came to gaps between documented procedures and real-world practices and, as a result, unmasked opportunities that might have been missed with a purely technical analysis.

Moving from insight to action

While AI was one area of focus, we remained technology-agnostic and first focused on finding the key problems regardless of which tools would get the job done. This balanced strategy proved effective: Algol's teams took the process improvements and workflow enhancements under their internal development roadmap while we provided deeper technical expertise for data-driven and AI-enabled initiatives. This dual-track allowed for immediate operational gains while laying the essential groundwork for more sophisticated technological solutions that required additional infrastructure and preparation.

A particular area of interest for Algol was to gain a better understanding of how they could leverage generative AI to streamline operations. Our job was to help them not only identify opportunities but also support the company in a strategic approach to implementation. 

From an initial pool of over 70 improvement ideas gathered from both front-line staff and management, we helped Algol methodically evaluate and prioritize initiatives based on business impact, technical feasibility, and available resources.

We looked at each potential solution through three critical perspectives: business impact, user value, and technical feasibility. While some proposals showed promise, data limitations or technical constraints meant they weren't immediately actionable. Instead, we focused on identifying initiatives that offered the optimal balance of impact and implementation complexity. Through a methodical evaluation process, we winnowed our initial pool of opportunities, first to 15 initiatives, then to eight, before finally selecting a small handful of potential projects that promised the greatest value with the highest likelihood of success when it came to implementation.

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