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From Big Data to Big Business - Using the Research-based DataProfit model for Data-driven Growth

Denne idé er en del af The Future of Nordic Manufacturing

19. juli 2017

"Idea in Brief:

Problem: There is an enormous profit potential for manufacturing firms in big data, but one of the key barriers to obtaining data-driven growth is the lack of knowledge about which capabilities are needed to extract value and profit from data.

Solution: We (BDBB research group at CBS) have developed a research-based capability mapping tool, entitled DataProfit, which the public business consultants can use to upgrade their tool kit to enable data-driven growth in manufacturing organizations.

Benefit: The DataProfit model/tool comprises insights of an extensive research project that has been developed and tested in a multitude of manufacturing organizations – thus making it both a proven solution and a new idea. Moreover, resources for the application of the model are freely available online.


The Problem:
As digital developments accelerate and we see new advances in analytics on almost a daily basis, data-driven business opportunities are increasingly presumed to carry enormous profit potential for many industries - particularly the manufacturing sector (Ritter, 2015, 2017). Yet, realizing this potential may seem like an insurmountable challenge, as few successful business cases can be found; that is, corporate ambitions of becoming data driven abound, but many firms still seem to struggle in obtaining a competitive advantage from their data-driven efforts (Ritter, Pedersen and Sørensen, 2017a, 2017b). For example, it has been documented that “big data” is not in itself sufficient to protect a company from its competition, as organizations need the right managerial tool kit to extract the value from data (Lambrecht and Tucker, 2017). In a similar vein, it has been found that an essential barrier to data-driven growth among manufacturing organizations is a lack of knowledge about which organizational capabilities are needed to obtain data driven growth (Ritter and Poulsen, 2015).

The Solution:
Consequently, we have been mapping the capabilities that are needed to obtain data-driven growth in an extensive and large-scale research project at Copenhagen Business School entitled “From Big Data to Big Business” (supported by Industriens Fond). We have turned these insights into a simple and practical capability mapping tool which we call “DataProfit”, which manufacturing organizations can utilize to score and rate their standing on the respective capabilities, and thereby obtain an “organizational profile” for how capable the organization is to obtain data-driven growth. We have also outlined how internal workshops in the model/tool can be carried out in organizations. Moreover, the model/tool has been developed in cooperation with over 40 organizations, and the applicability of the tool has been tested in several company workshops. Hence, DataProfit is (i) a research-based tool (ii) developed in close collaboration with, and for the use in, manufacturing firms (iii) that has been tested in practice, and (iv) which addresses a central barrier for data-driven growth (that is, the lack of knowledge into which capabilities are needed).

We therefore propose that the public business consultants enhance their knowledge and skills by utilizing our framework which is available for free download (as it is supported by Industriens Fond) in the following link: https://www.saxo.com/dk/dataprofit-kompetencekort-for-datadreven-vaekst… (Danish version - the English version is available here: https://www.saxo.com/dk/dataprofit-a-capability-map-for-data-driven-gro… ).

The link is to our “practitioner’s guide” to the tool, and it is entitled “DataProfit: Kompetencekort for Datadreven Vækst (Praksisguide)”. It provides a step-by-step guide into the nine capabilities that we have identified as essential for data-driven growth, and organizations can rate themselves as they go through the nine capabilities. We similarly provide an outline for how a workshop might look like, who should be invited, and which questions are relevant to ask. Consequently, our research has provided a research-based and field tested repository of insights for manufacturing firms to obtain profitable data-driven growth. Moreover, the framework is easily accessible for practitioners, as it is simple and relevant. Therefore, we argue that it can be utilized to improve the knowledge and skills of the public business consultants, and that they can utilize it to improve the data-driven efforts of the manufacturing sector.

Put differently, we have built a research-based self-assessment tool that manufacturing firms can utilize to rate themselves on in relation to nine specific capabilities that are needed to realize the full potential in data-driven growth. The output of this tool is a ""visual profile"" that visualizes how well the organization currently performs on the nine capabilities. Thus, the profile provides visual capability mapping that can illustrate where the organization should improve its efforts in order to commercialize big data. Moreover, it is possible to include multiple respondents from the respective organization (for instance different departmental or functional areas) which can shed light on differences in opinions within the organization. Consequently, the business consultants can utilize the tool to (i) analytically assess the current situation of the manufacturing firm (ii) see areas that need improvement or further attention, and (iii) structure company workshops around the tool.

More info about the tool here: https://ing.dk/artikel/tag-testen-din-virksomhed-dataklar-200670 and here http://customerthink.com/why-data-driven-growth-is-so-difficult/

Why should it work – and what is the benefit?
As our work with the DataProfit model is research-based, it is both a proven solution and a new idea. It is a proven solution as we have developed the model, and tried it out in practice, with various manufacturing firms. It is a new idea, as the model is one of the first academically-based frameworks for capability mapping for data-driven growth in manufacturing organizations. Hence, the benefit lies in the proven relevance of this novel and research-based model/tool.

How could the public business consultants use the DataProfit tool?
We suggest that the public business consultants utilize the workshop format that we describe in the guide - and have workshops at the manufacturing organizations where they:

- Invite relevant employees representing the nine different capabilities.
- Let them assess their performance on each capability.
- Visualize the overall DataProfit profile.
- Discuss ambitions, plans and projects for future data-driven growth.

All of these aspects are described in a simple step-by-step manner in the guide. Hence, the learning curve should not be steep. However, we can be helpful in the training of the consultants by e.g. Providing an introductory session into the tool and its application.

How does the proposed solution benefit key stakeholders? The proposed solution benefits the various stakeholders in the Nordics in several ways: (i) The public business consultants obtain a research-based framework and format to provide better counseling within data-driven development (ii) the manufacturing companies obtain standardized and tried counseling into their current status and future potential, and (iii) the Nordic manufacturing sectors should obtain data-driven growth for the benefit of all.

Resources that are Available:
As noted above, various resources are available from our project to the public business consultants in their endeavor to help manufacturing organizations. They are as listed below:
- “DataProfit: Kompetencekort for Datadreven Vækst (Praksisguide)” – Link: https://www.saxo.com/dk/dataprofit-kompetencekort-for-datadreven-vaekst… (Danish version).

- ""Dataprofit: A capability map for data-driven growth"" - link: https://www.saxo.com/dk/dataprofit-a-capability-map-for-data-driven-gro… (English version).

- Our website with background into the research project, and additional insights: http://blog.cbs.dk/bigdata/

- Additional material for DataProfit, such as posters for workshops: http://blog.cbs.dk/bigdata/dataprofit/

- Insights into the contextual developments related to the framework, i.e. ""The five waves of big data"": http://blog.cbs.dk/bigdata/kompetencecenter/defembølger/ and http://jyllands-posten.dk/debat/kronik/ECE7586842/Bliver-big-data-til-b…

- Insights on the role of salespeople and customers in data-driven growth: http://www.businessdanmark.dk/Inbusiness-forside/InBusiness-artikelarki…

Background Info on the Model and Research:
In the model, we apply Winter’s (2003, p. 991) notion of a capability as “a high-level routine (or collection of routines) that, together with its implementing input flows, confers upon an organization’s management a set of decision options for producing significant outputs of a particular type”. Based on this definition, we have identified nine capabilities that are needed to obtain data-driven growth and success. The nine capabilities are subdivided into three broad dimensions: BASIS (the capabilities that are needed as an absolute minimum to work with data), ORGANIZATION (the capabilities that revolve around the organizational context for working with data), and APPLICATION (the capabilities that describe how to actually make money on data). Each of the three dimensions entails three capabilities, and therefore, it becomes a 3x3 model. The nine capabilities are as follows (as intricately described in Ritter, Pedersen and Sørensen, 2017a, 2017b):

1. BASIS: Data capability, i.e. a firm’s routines for collecting, storing and making data available;
2. BASIS: Analytics capability, i.e. a firm’s routines for analyzing, reporting and visualizing results;
3. BASIS: Permission capability, i.e. a firm’s routines for securing lawful and a societally acceptable treatment and application of data;
4. ORGANIZATION: Strategy capability, i.e. a firm’s routines for developing, communicating and executing a data-driven strategy;
5. ORGANIZATION: Autonomy capability, i.e. a firm’s routines for giving freedom to employees to experiment as well as routines to secure autonomous spaces for employees;
6. ORGANIZATION: Business development capability, i.e. a firm’s routines for analyzing/preparing and implementing/supporting growth opportunities;
7. APPLICATION: Optimization capability, i.e. a firm’s routines for applying data to existing processes in order to make these processes more efficient;
8. APPLICATION: Cross sales capability, i.e. a firm’s routines for understanding new data-driven needs among existing customers, designing suitable data-driven value propositions for them, and convincing the customers to buy the new value propositions;
9. APPLICATION: Upcycling capability, i.e. a firm’s routines for exploring new uses of old data and exploiting these new uses to reach new customers and new markets.

Further info:






Lambrecht A, Tucker C. 2017. Can Big Data Protect a Firm from Competition? CPI Chronicle. Available at https://www.competitionpolicyinternational.com/can-big-data-protect-a-f…

Ritter T. 2015. Bliver big data til big business? Available at http://jyllands-posten.dk/debat/kronik/ECE7586842/Bliver-big-data-til-b…

Ritter T. 2017. Why Data-Driven Growth is so Difficult. CustomerThink. Available at http://customerthink.com/why-data-driven-growth-is-so-difficult/

Ritter T, Pedersen CL. 2017. Test din og kundens digitale modenhed. Available at http://www.businessdanmark.dk/Inbusiness-forside/InBusiness-artikelarki…

Ritter T, Pedersen CL, Sørensen HE. 2017a. DataProfit: Kompetencekort for Datadreven Vækst (Praksisguide). Available at https://www.saxo.com/dk/dataprofit-kompetencekort-for-datadreven-vaekst…

Ritter T, Pedersen CL, Sørensen HE. 2017a. Dataprofit: A capability map for data-driven growth. Available at https://www.saxo.com/dk/dataprofit-a-capability-map-for-data-driven-gro…

Ritter T, Pedersen CL, Sørensen HE. 2017b. Capabilities for Data-driven Growth in B2B Firms. Paper accepted for presentation at the 22nd CBIM Academic Workshop 2017.

Ritter T, Poulsen CM. 2015. Sådan bruger du Big Data i din virksomhed. Available at http://finans.dk/live/opinion/debatindlaeg/ECE8197679/S%C3%A5dan-bruger…

Winter SG. 2003. Understanding dynamic capabilities. Strategic Management Journal 24(10): 991-995"