Chasing the rainbow: towards an experimental methodological framework for the assessment of digitalisation at the firm level

Ferraz, João Carlos

doi:10.20396/rbi.v22i00.8668376

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ARTICLE Seção Especial - Digitalização da Indústria (DIGIND) • Rev. Bras. Inov. 22 • 2023 • https://doi.org/10.20396/rbi.v22i00.8668376 copy

Chasing the rainbow: towards an experimental methodological framework for the assessment of digitalisation at the firm level

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

This paper proposes a methodological framework for assessing the adoption of digital technologies by industrial firms. Given the increasing economic importance of digital technologies, proper assessment methods are required. However, evaluating digital adoption can be quite challenging due to the pervasiveness, intangibility, and fast progress rate of such technologies. The proposed framework is designed to enable three tasks: (i) registering information about current and prospective adoption of digital technologies by industrial firms, (ii) developing indicators to capture the dynamics of digital adoption in time; and (iii) analysing digitalisation determinants, requirements, and outcomes. This paper contributes to building a reference framework to evaluating how digital technologies can strengthen the industrial development of nations, particularly developing countries.

KEYWORDS
Technical progress; Digitalisation; Industry; Survey; Analytical framework

Dimension	Topics	Scope	Element
Product	User experience	Digital products and services must offer usability and aesthetic properties designed to evoke user engagement	Usability
			Aesthetic
			Engagement
	Value proposition	Digitalisation implies a value proposition articulated with customer segmentation, including pricing, product portfolio positioning, articulation with sales channels.	Targeting
			Bundling
			Commissions
Environment	Monitoring digital evolution	Digital solutions must enable firms to monitor their environment, by collecting data about marketing channel performance and user behaviour.	Devices
			Channels
			Behaviour
Organisation	Skills	Internal and external skills appropriate to the firm for the intended digital functions, promoting continuous learning on the properties of digital technologies.	Learning
			Roles
			Teams
	Improvising	The flexibility and low cost of digital technologies can provide improvisational experiences.	Space
			Time
			Coordination

Type	Examples	Digital Resources	Organisational structure	Digital growth strategies	Metrics	Objectives
Spot Digitalisation	Automated routines and tasks	Digital assets	Standard top-down hierarchy	Market penetration	Traditional Critical Performance Indicators (KPIs)	Efficient deployment of resources to existing activities
Integrated Digitalisation	Addition of digital components to the product or service.	Digital assets + digital agility	Agile and separate units	Market penetration + Platform-based market actions	Traditional and digital KPIs: user experiences	Revenue increase, enhanced customer experience
Digital transformation	Introduction of new business models	Digital assets + digital agility + Big Data Analytics	Separate units with flexible organizational forms	Market penetration + Platform-based market actions + Platform diversification	Digital KPIs: digital participation	New cost-revenue model

Strategy	Capabilities	Organisation	Culture
Awareness of change	Digital marketing and sales	Structure	Agility
Long-term ambitions and aspirations	Customer journeys	Collaboration between business practices and technology	Testing and learning
Business and digital strategy	Data and analytics	Talents	Experimentation
Customer centrality	Technology platform	Proficiency in analytics and digital	Internal collaboration
Growth opportunities	Focus on value creation	Governance and metrics	External orientation
Firm-specific roadmap			Data-driven mindset

Function/Stage	Digital Novice	Vertical Integrator	Horizontal Collaborator	Digital Champion
Business models, products & service portfolio	First digital solutions and isolated applications	Digital product and service portfolio with software, network (m2M) and data as key differentiator	Integrated customer solutions across supply chains boundaries; collaboration with external partners	Development of new disruptive business models with innovative product and service portfolio
Market access & customer	Online presence is separated from offline channels; focus on products instead of customers	Multichannel distribution with integrated use of online and offline channels; data analytics deployed	Individualized customer approach and interaction with value chain partners	Integrated customer journey management across all digital marketing and sales channels with customer empathy and CRM
Value Chain & Processes	Digitised and automated subprocesses	Vertical digitization and integration of process and data flows within the company	Horizontal integration of processes and data flows with customers and external partners; intensive data use	Fully integrated partner ecosystem with self-optimised, virtualized processes; decentralized autonomy
IT Architecture	Fragmented IT architecture in house	Homogenous IT architecture inhouse	Common IT architectures in partner network	Partner service bus; secure data exchange
Compliance, Legal, Risk, Security & Tax	Traditional structure, digitisation not in focus	Digital challenges recognized but not comprehensively addressed	Legal risk consistently addressed with collaboration partners	Optimizing the value chain network
Organization & Culture	Functional focus in silos	Cross functional collaboration but not structured and consistently performed	Collaboration across company boundaries, culture, and encouragement of sharing	Collaboration as a key value driver

Function/Stage	I	II	III	IV	V
Data processing in the production	No processing of data	Storage of data for documentation	Analysing data for process monitoring	Evaluation for process planning / control	Automatic process planning / control
Machine-to-machine communication (M2M)	No communication	Field bus interfaces	Industrial ethernet interfaces	Machines have access to internet	Web services (M2M software)
Companywide networking with the production	No networking of production with other business units	Information exchange via mail /telecommunication	Uniform data formats and rules for data exchange	Uniform Data formats and inter-divisionally linked data servers	Inter-divisional, fully networked IT solutions
ICT infrastructure in production	Information exchange via mail telecommunication	Central data servers in production	Internet-based portals with data sharing	Automated information exchange (e.g. order tracking)	Suppliers / customers are fully integrated into the process design
Man-machine interfaces	No information exchange between user and machine	Use of local user interfaces	Centralized /decentralized production monitoring / control	Use of mobile user interfaces	Augmented and assisted reality
Efficiency with small batches	Rigid production systems and a small proportion of identical parts	Use of flexible production systems and identical parts	Flexible production, systems and, modular designs for the products	Component-driven, flexible production of modular products within the company	Component-driven, modular production in value-adding networks

Korean Stage	German Level	Implementation
Basic	Lv.1~Lv.2	Basic logistics information collection level using barcode and RFID. Quality history management through lot-tracking. Partial process automation.
Intermediate 1	Lv.2~Lv.3	Real-time data collection from the facility and monitoring. Real-time information exchange based on information management and factory operation.
Intermediate 2	Lv.4~Lv.5	Automation of facility control. Real-time decision making and direct facility control.
Advanced	Lv. 5	Intelligent production with self-diagnostics and control using CPs, IoT, and big data. Real-time customised service through value chain.

2002 Version	2021 Version
% Employees using computers in their normal work routine (at least once a week):	% Employees with access to internet for business purposes
Does your enterprise use or plan to use Internet?	% Employees using a portable device provided by the enterprise
Type of external connection to the Internet in 2001? (Mobile phone, modem, ISDN, xDSL, Other fixed connection) Question range: less than 2 Mbps to at least 2 Mbps.	Does your enterprise use any type of fixed line connection to the internet? (ADSL, SDSL, VDSL, fiber optics technology, cable technology, etc.)? What is the maximum contracted download speed of the fastest fixed line internet connection? (Question range: Less than 30 Mbps to at least 1Gbps)
Does the enterprise have a Web site or homepage?	Does your enterprise have a website?
	Does your enterprise use social media?
What percentage of the total turnover did Internet sales represent in 2001?	% Turnover generated by web sales of goods or services, in 2020.
Breakdown of Internet sales in 2001 by destination (own country, EU, World)	Web sales to customers located in (own country, EU, World)
Did the enterprise use EDI or networks other than Internet?
What percentage of the total sales (in monetary terms) did the sales via EDI or networks other than Internet represent in 2001?	During 2020, did your enterprise have EDI-type sales of goods or services?
Problems and barriers related to on-line sales (Much important, some importance, not important, don´t know): Products, customers not ready, security over payments, legal uncertainty, logistics	What percentage of total turnover was generated by EDI-type sales of goods or services, in 2020?


	Does your enterprise use ERP software?
	Does your enterprise buy any cloud computing services used over the internet? (Email, office software, finance, database, computing power, etc
	Does your enterprise use interconnected devices or systems that can be remotely controlled via the internet (Internet of Things)? (Energy, security, logistics, maintenance)
	Does your enterprise use any of the following Artificial Intelligence technologies? (Text mining, language Generation, deep learning, robotics, sales)
	Does your enterprise use Artificial Intelligence software or systems for any of the following purposes? (Marketing or sales, production processes, organisation of business administration processes, management of enterprises, logistics, ICT security, human resources management or recruiting)

In the last 12 months, were Big Data analytics undertaken from the following sources of data?	YES	NO
Company data from intelligent devices or sensors, such as data exchanges between machines, digital sensors, radio frequency identification labels, etc.
Geolocation data from the use of portable devices such as mobile phone, wireless connection, or GPS
Data generated from social media such as social networks, blogs, or multimedia content sharing sites
Other Sources of Big Data

In 2017, how much of each type of information was kept in digital format at this business? (Select one for each row)
Business functions/Intensity	None	Up to 50%	More than 50%	All	Don´t know	This type of information not collected by this business
Personnel
Financial
Customer feedback
Marketing
Supply chain
Production
Other

In 2017, to what extent did this business use the following technologies in producing goods or services? (Select one for each row)
Digital technology/intensiveness	No use	Testing, but not using in production or service	In use for less than 5% of production or service	In use between 5% - 25% of production or service	In use for more than 25% of production or service	Don´t know
Augmented reality
Automated guided vehicles
Automated storage and retrieval systems
Machine learning
Natural language processing
Radio-frequency identification inventory systems
Robotics
Touchscreen/kiosks for customer interface

Digital Generation/Business Function	Relations with suppliers	Process management	Relations with clients
G1	Manual transmission of orders (e.g., fax)	Stand-alone automation	Spread sheet registry of contacts
G2	Electronic transmission of orders (e.g., email)	Partially or fully integrated CAD-CAM	Automated devices to support sales
G3	Digital system for processing orders, stocks & payments	Process execution automated system	Internet based support for sales & after services
G4	Real time web-based relation	Machine to Machine -M2M system	Client relationship based online monitoring product use

Universidade Estadual de Campinas Rua: Carlos Gomes, 250. Bairro Cidade Universitária, Cep: 13083-855 , Campinas - SP / Brasil , Tel: +55 (19) 3521-5176 - Campinas - SP - Brazil
E-mail: rbi@unicamp.br

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[1] Author’s contribution:

A. Literature review and problematization: João Carlos Ferraz B. Data collection and statistical analysis: João Carlos Ferraz C. Preparation of figures and tables: João Carlos Ferraz D. Manuscript development: João Carlos Ferraz E. Bibliography selection: João Carlos Ferraz