How Can SMEs Benefit from Big Data? Challenges and a Path Forward. (11th May 2016)
- Record Type:
- Journal Article
- Title:
- How Can SMEs Benefit from Big Data? Challenges and a Path Forward. (11th May 2016)
- Main Title:
- How Can SMEs Benefit from Big Data? Challenges and a Path Forward
- Authors:
- Coleman, Shirley
Göb, Rainer
Manco, Giuseppe
Pievatolo, Antonio
Tort‐Martorell, Xavier
Reis, Marco Seabra - Other Names:
- Vicario Grazia guestEditor.
Tort‐Martorell Xavier guestEditor. - Abstract:
- Abstract : Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the 'state‐of‐the‐art' of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and businessAbstract : Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the 'state‐of‐the‐art' of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd. … (more)
- Is Part Of:
- Quality and reliability engineering international. Volume 32:Number 6(2016:Oct.)
- Journal:
- Quality and reliability engineering international
- Issue:
- Volume 32:Number 6(2016:Oct.)
- Issue Display:
- Volume 32, Issue 6 (2016)
- Year:
- 2016
- Volume:
- 32
- Issue:
- 6
- Issue Sort Value:
- 2016-0032-0006-0000
- Page Start:
- 2151
- Page End:
- 2164
- Publication Date:
- 2016-05-11
- Subjects:
- predictive analytics -- maturity model -- data science -- skills shortage
Reliability (Engineering) -- Periodicals
Quality control -- Periodicals
High technology -- Periodicals
620.00452 - Journal URLs:
- http://www3.interscience.wiley.com/cgi-bin/jhome/3680 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/qre.2008 ↗
- Languages:
- English
- ISSNs:
- 0748-8017
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7168.137300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 463.xml