(Big) data is everywhere nowadays and most if not all of the key players of various industries and fields have started integrating it in every aspect of their businesses from digital marketing to fraud detection. (10. Statista survey 2023)
But are you a part of it? Are you surfing the big data wave or just swimming in its wake?
If you are a small to medium business owner or IT professional wondering whether or how to start integrating data analysis in your business operations then this blog post is for you.
Introduction
In this blog post we will focus on big data analysis for small and medium businesses and what are the main barriers for adoption of big data followed by a set of recommendations on how you could proceed to make your big data dreams a reality.
Big data for SMEs
As stated before, big data analysis is now a crucial part of most big businesses operations, however an array of factors might make it (or at least sound like it is) more difficult for small businesses to jump on the wagon.
These main factors are but not limited to :
- Lack of data professionals in the company
- Small volume of company generated data
- Information system architecture not built with data (storage, processing and visualization) in mind and a lack of budget for technology related solutions
- Reluctance or doubt about the benefits of big data for small scale businesses from leadership or employees (resistance to change)
- Legal risks (RGPD in europe and LPD in Switzerland for instance)
(5.Willets et al. 2020, 3.Coleman et al. 2016, 4.Shah et al. 2017)
However, contrary to common representation, SMEs, due to their size, more flexible structure and processes and greater agility (smaller and more approachable chain of commands, direct communication between leadership and operations, etc…..) might be better equipped for a quick and thorough adoption of big data in their day-to-day operations (1.Sen et al. 2016, 2.Iqbal et al. 2018).
Recommendations for adoption
Now that we have stated the main barriers for adoption let’s get to the more (hopefully) interesting and useful part : our recommendations on how to integrate big data into your business operations.
Our recommendations are built around two pillars :
- Employees
- Infrastructure
With a focus on :
- Obtaining buy-ins from employees and leadership in order to reduce “change management” related issues
- Keep the cost of ownership of the information system as low as possible
Your employees are your best asset (and soon your data will too)!
Addressing lack of data proficient employees and adoption reluctance :
From bootcamps to online training, the offer in data related formations has grown “exponentially” the last few years. Use these to train your employees on company time to transform them into data professionals that can be actors rather than only executants and provide you with insight on how to best integrate big data in your company context.
Make presentations on how big data will make your employees more efficients and how training will boost their future employability in order to make them more engaged and enthusiastic about the digital transformation of your business. (6.Ahmed et al. 2019)
Explain to your employees and leadership what big data could bring to your company and how it will positively impact every aspect of it. (6.Ahmed et al. 2019)
Dealing with low volume of data and inadequate information systems :
At the beginning your data collection capabilities will be limited, one solution to that could be to initiate a “data gathering” initiative where your IT staff will make an inventory of every existing data (from spreadsheets to long forgotten databases) and encourage every employee to make available the data they have collected.
Make data collection a standard practice in your day-to-day operations so it feels natural for employees to gather and log every bit of data they come across. In that regard your information system will be one of your main facilitators, use existing products or develop simple interfaces to make data entering painless and as less time consuming as possible in order to lessen employee reluctance.
Have your IT staff or external consultants audit your existing information system so it can be redesigned with a more data centric approach : (8.Ramakrishnan et al. 2012)
- Homogeneous and centralized data storage to prevent siloting of data and to make the creation of a proper data lake easier)
- Integration of data visualization and querying solutions to boost the ease of use of your newly gathered data
- Use of open source solutions to prevent vendor lock-in, keep cost of ownership low and facilitate retrieval for integration with other components of your information system
Understanding and mitigating legal risks associated with big data (european context)
Have a presentation about data legal requirements for your employees and manager.
Use external consultants to audit and catalog your current and future data infrastructure.
Rely as much as possible on self hosted solutions to minimize legal risks and enhance RGPD information retrieval requests protocol.
Appoint a data management officer in order to centralize the tracking of your data and ensure a proper conformity with the current data laws.
Conclusion
In this blog post we tried to enumerate barriers for adoption of big data in small business and to propose a set of recommendations to workaround these possible obstacles.
References
Sen, D., Ozturk, M. and Vayvay, O., 2016. An overview of big data for growth in SMEs. Procedia – Social and Behavioral Sciences, 235, pp.159-167. https://doi.org/10.1016/j.sbspro.2016.11.011.
M. Iqbal, S. H. A. Kazmi, A. Manzoor, A. R. Soomrani, S. H. Butt and K. A. Shaikh, “A study of big data for business growth in SMEs: Opportunities & challenges,” 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), Sukkur, 2018, pp. 1-7, doi: 10.1109/ICOMET.2018.8346368.
Coleman, S., Göb, R., Manco, G., Pievatolo, A., Tort-Martorell, X., and Reis, M. S. (2016) How Can SMEs Benefit from Big Data? Challenges and a Path Forward. Qual. Reliab. Engng. Int., 32: 2151–2164. doi: 10.1002/qre.2008.
Shah, S., Soriano, C. B., & Coutroubis, A. D. (2017). Is big data for everyone? the challenges of big data adoption in SMEs. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). doi:10.1109/ieem.2017.8290002
Willetts, M., Atkins, A. S., & Stanier, C. (2020). Barriers to SMEs Adoption of Big Data Analytics for Competitive Advantage. 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS). doi:10.1109/icds50568.2020.9268687
Ahmed F, Qin YJ, Martínez L. Sustainable Change Management through Employee Readiness: Decision Support System Adoption in Technology-Intensive British E-Businesses. Sustainability. 2019; 11(11):2998. https://doi.org/10.3390/su11112998
Chaudhry, Smita (2018) “Managing Employee Attitude for a Successful Information System Implementation: A Change Management Perspective,” Journal of International Technology and Information Management: Vol. 27: Iss. 1, Article 3. https://doi.org/10.58729/1941-6679.1364
Ramakrishnan, T., Jones, M.C. and Sidorova, A., 2012. Factors influencing business intelligence (BI) data collection strategies: An empirical investigation. Decision Support Systems, 52(2), pp.486-496. https://doi.org/10.1016/j.dss.2011.10.009.
Fischer, G. (2020). Guidelines for SME adaption to GDPR Case study of Evalent.
Nasrollahi M, Ramezani J, Sadraei M. The Impact of Big Data Adoption on SMEs’ Performance. Big Data and Cognitive Computing. 2021; 5(4):68. https://doi.org/10.3390/bdcc5040068
Maroufkhani, P., Wan Ismail, W.K. and Ghobakhloo, M., 2020. Big data analytics adoption model for small and medium enterprises. Journal of Science and Technology Policy Management, 11(4), pp.483-513. https://doi.org/10.1108/JSTPM-02-2020-0018
Singh, N.P. and Singh, S., 2019. Building supply chain risk resilience: role of big data analytics in supply chain disruption mitigation. Benchmarking: An International Journal, 26(7), pp.2318-2342. https://doi.org/10.1108/BIJ-10-2018-0346.
Ciasullo, M.V., Montera, R. and Douglas, A., 2022. Building SMEs’ resilience in times of uncertainty: the role of big data analytics capability and co-innovation. Transforming Government: People, Process and Policy, 16(2), pp.203-217. https://doi.org/10.1108/TG-07-2021-0120
Maroufkhani, P., Iranmanesh, M. and Ghobakhloo, M., 2023. Determinants of big data analytics adoption in small and medium-sized enterprises (SMEs). Industrial Management & Data Systems, 123(1), pp.278-301. https://doi.org/10.1108/IMDS-11-2021-0695
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