Overview of chemical
trends.

An analysis of future trends of particular relevance to the chemical and pharmaceutical industry.

Overview of the analyzed trends

15 trends were identified.

Trends are nothing other than movements of change or processes of transformation, that shape the future world with their far-reaching influences on business, societies, economies, cultures and personal lives. You can find trends at a wide variety of penetration levels. This report showcases 15 selected trends that have already have, or are expected to have, a major impact on operational processes and the world of work in an operational and organizational way in the chemical and pharmaceutical industry. The 15 trends are clustered into three categories.

The 15 trends explained.*

Trends have a major impact on the development of existing and new skills. In order to better understand trends and link them to HR strategy or development measures, relevant skills are assigned to the trends below.

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*Source: HRForecast data crawled from public sources (regions: Germany, EU, USA & China). Period analyzed: 01/2018 – 12/2019. Only data from the chemical & pharmaceutical industry was analyzed.

Digital technologies

  • Skill
  • Definition
Big data technologies
Definition:

The processing of complex, large and dynamic amounts of data with modern data processing technologies.

Practical example:

Development of a database of all sorts of materials from experimental and computational chemistry.

Blockchain
Definition:

Systems in which a record of transactions are maintained across several computers that are linked in a peer-to-peer network.

Practical example:

Blockchains help track, trace, and deliver processed chemicals and ensure quality or detect counterfeit chemicals with transaction data.

Cyber security
Definition:

The practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks.

Practical example:

Cybersecurity aims to protect production assets, valuable chemical formula information and customer data bases from unauthorized access.

Data science & analytics
Definition:

An inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structured and unstructured data.

Practical example:

Analyzing diverse data sources, such as experiments, photos and images to predict the chemical structure of a material.

Machine learning / A.I.
Definition:

The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making.

Practical example:

Simulating chemical reactions during the search for new materials, decreasing the time to develop by reducing the number of laboratory trials needed.

Material technologies

  • Skill
  • Definition
3D printing

Definition:

3D printing, also known as additive manufacturing, is the construction of a three-dimensional object from a CAD model or a digital 3D model.

Practical example:

In case of an asset failure due to a damaged part, the replacement part can be conveniently printed on spot and installed in time. In-house printing of spare parts reduces inventory costs and increases efficiency.

Alternative feedstock

Definition:

The transition from petroleum and natural gas feedstocks to alternative, largely bio-based feedstocks.

Practical example:

Biomass as a renewable energy source, derived from plants and organisms that can be converted into fuel for energy, chemicals and polymers.

Batteries

Definition:

Containers consisting of one or more cells, in which chemical energy is converted into electricity and used as a source of power.

Practical example:

Battery materials, such as advanced cathode active materials improve battery perfor- mance in terms of energy density and efficiency, which translates into a safer battery.

Biotechnology

Definition:

A broad area of biology, involving the use of living systems and organisms to develop or make products.

Practical example:

The development of mRNA vaccination materials.

Material sciences

Definition:

The interdisciplinary field of materials science, also commonly termed materials science and engineering is the design and discovery of new materials, particularly solids.

Practical example:

Nanomaterials – materials with a structure at the nanoscale and unique optical, electronic, thermo-physical or mechanical properties.

Interaction & business processes

  • Skill
  • Definition

Agile principles

Definition:

Agile principles aim at being able to act flexibly and, moreover, proactively, anticipatively and proactively in an organization in order to introduce necessary changes.

Practical example:

Agility emerged as project management methodology and then migrated into organizational and cultural transformations. In chemical product development, common agile methods are Scrum and Kanban.

Automation & robotics

Definition:

The usage or introduction of automatic equipment in a process.

Practical example:

Cobots (collaborative robots) can be utilized to optimize the collaboration between humans and robots in a shared space, e.g. while aiding a chemical technician in hazardous laboratory experiments.

Digital sales

Definition:

The ability to scale relationship building using social and digital  channels.

Practical example:

Implementation of e-commerce platforms and marketing automation tools to attract clients via multiple channels, to scale client touchpoints, decrease costs and improve supply chain efficiency.

Internet of things & connectivity

Definition:

Describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet.

Practical example:

Sensors collecting data of production machines enable scalable data analytics that lead to optimized and predictive maintenance of machines, saving costs, increasing efficiency and allowing remote monitoring.

Virtual and augmented reality

Definition:

Technology that superimposes a computer-generated image on a user’s view of the real world, thus providing a composite view.

Practical example:

Provides maintenance technicians the capability to provide effective training and feedback to staff remotely in real-time through hardware and software.

Drivers of change in the chemical and pharmaceutical industry

One in four job postings requires skills in the area of data science & analytics.*

The 15 analyzed trends are in different maturity stages, hence the impact on the industry varies greatly. Three phases can be defined (emerging, maturity, adoption phase).

4 of of 15 trends

High-impact trends – adoption phase: wide, large-scale adoption across the whole value chain with high impact on the industry today.

4 of of 15 trends
Medium impact trends – maturity phase: beginning process of maturation that moderately impacts the industry today and an expectation that the trends will lead to being the new state of the art in the coming years.
7 of of 15 trends

Low impact trends – emerging phase: still in an embryonal stage and therefore no concrete benefits yet in terms of agility, scalability and flexibility. Low impact on the industry today but close monitoring of trends recommended as they might emerge to impact the jobs in the industry in the short to mid-term future.

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*Source: HRForecast data crawled from public sources (regions: Germany, EU, USA & China). Period analyzed: 01/2018 – 12/2019. Only data from the chemical & pharmaceutical industry was analyzed.

Share of the trends on all job postings

The trend with the highest impact on the industry is ‘data science & analytics’. Around one in four job postings requires skills in this area. The three other trends that have a very high impact on the industry are biotechnology, digital sales and machine learning/AI. Ca. one of six job postings requires skills in each of these 3 areas.

Drivers of change in the chemical and pharmaceutical industry

Impact of the trends on the functional areas.

Green header

Name of functional area.

White body

List of relevant trends in functional area.

Grey footer

Additional explanations.

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*Source: HRForecast data crawled from public sources (regions: Germany, EU, USA & China). Period analyzed: 01/2018 – 12/2019. Only data from the chemical industry was analyzed.

High impact
Research & dev.

Large data repositories provide intuitive access to data and free up R&D time for more creativity and productivity.

Purchasing

Implementation of blockchain platforms to ease, validate and accelerate contract management and material negotiation processes .

High impact
Production

Collecting and processing data from sensors and utilizing robots to automate the production workflows.

High impact
Maintenance

Algorithms that process continuous streams of sensor data to analyse, predict, and visualize data for improved maintenance of production lines, also known as predictive maintenance.

Logistics

Continuous collection and analysis of internal data (e.g. historic material consumption) and external data (e.g. tariff regulations, business cycles) to predict future material demands and bottlenecks for the supply chain.

Sales

Prediction of customer behavior to recommend appropriate products to customers through e-commerce platforms based on the customer’s buying pattern and requirements.

Marketing

Machine Learning techniques used to improve customer segmentation and predictive analytics to qualify and prioritize leads based on the segmentation.

High impact
IT

The development of innovative, data-driven business models is transforming the IT function from a support function towards an essential value-driver in the value-chain of the organization.

Administration

Replacing repetitive, manually performed processes with automation technologies.

Human resources

Analysis of employee data in connection with business data to better understand the workforce, e.g. detecting skill gaps, modelling future workforce supply or understanding drivers for churn.