Data management for SMEs is more necessary today than ever. In fact, an important effect of the development of IT and the Internet is to make the use of data available to any organization. Consequently, making vital data-driven decisions for business success is no longer the exclusive privilege of large corporations. Small and medium-sized companies can and should also take advantage of data management.
Today, exploiting the advantages of data generated by on- and offline channels is imperative for companies to add value to their offerings. The 2019 State of Digitalization Survey published by Vodafone revealed that SMEs, microenterprises and freelancers had plenty of digital resources. Specifically: internet and device-to-device connectivity, 83% and 75%, respectively; collaboration platforms (79% and 60%), IoT through everyday devices (57% both). They also have cloud and hosting services (62% and 45%), websites and ecommerce (46% and 39%). To this we must add that, in several aspects, these percentages have increased due to the acceleration of digital transformation driven by Covid-19.
However, to carry out effective data management for SMEs it is essential to take into account the considerations that we summarize below.
Establishing a strategy: essential in data management for SMEs
Indeed, data management for SMEs and companies of all sizes requires an appropriate strategy. Only through an organized plan is it possible to successfully address the challenge of the 5 Vs of data: velocity, volume, variety, value and veracity. So establishing accurate policies and alignments will help to:
· Make data integration feasible.
· Avoid duplication, inconsistencies and redundancies in information.
· Increase performance when using data.
· Increase the reliability of the data for the accuracy of the analysis.
· Facilitate the making of appropriate decisions based on the data.
Accordingly, it is essential that this unique strategy includes very specific actions, among them:
Establish Data Governance
First, the enterprise must implement strong data governance. Data Governance defines the critical policies, procedures, technology, roles and responsible parties to define a single methodology for managing data assets. Therefore, those in charge of data governance must approve and communicate the guidelines, regulations, metrics and architecture applied to the processing of information. They must also monitor compliance with the guidelines and standards established in all areas and levels of the organization.
Specifying the data architecture
In essence, the data architecture comprises the development of the data management model. This includes the configuration of the data base, the storage and integration of the data, as well as the proposed architecture for the metadata. Necessarily, this process should anticipate alignment with third-party information processing models, such as suppliers, distributors and/or points of sale.
Ensuring data security
Today, data security is not limited to safeguarding information as a valuable corporate asset. It also involves safeguarding identity and data on customers and users, as established by the General Data Protection Regulation (GDPR). In this sense, guaranteeing data integrity and confidentiality is a priority that must be considered in the data management strategy for SMEs. In short, this concept encompasses all the actions necessary to preserve corporate data against threats of unauthorized access, queries and modifications.
Efficient management requires appropriate technology
We have said before that the digital transformation of companies goes beyond the incorporation of technology and involves changes in corporate culture. But, undoubtedly, data management involves the use of digital resources: network connectivity, infrastructure, hardware, CRM, ERP and even cloud computing, among others.
Similar to the digitization plan, the data management strategy for SMEs should consider the gradual incorporation of tools and solutions. All this allows to increase the capacity for the capture and processing of information. Therefore, it is important to anticipate such technology acquisitions to avoid a lag with respect to the established Data Governance and Data Management plan.
An essential task: integrating information
Specifically, this integration consists in the possibility of combining data from different sources in order to obtain a unified view of the information. For this purpose, solutions that enable the capture, cleansing, monitoring, adaptation and delivery of heterogeneous data in different formats are indispensable.
In itself, the idea is to achieve the convergence of data from supply chain, marketing, sales and administration into a central system. Including data captured on the website, apps and social networks. In addition, information from market research and other aspects inherent to the business, generated by consultants and even data from IoT sensors in physical stores. In this way, it is feasible to use the data as a whole and extract valuable information for decision making.
Maintaining quality: a must in data management for SMEs
In this context of data of different formats, characteristics and origins, how is it possible to ensure that the information acquires and maintains a standard of quality? To this end, in principle, it is necessary to avoid establishing information silos in the different departments within the company.
At the same time, in the treatment and management of information, it is critical to apply solutions capable of standardizing, deduplicating and enriching data. Through such technologies we can add value to the data in order to get the most out of it. This would consequently help us to increase efficiency, make informed decisions and strengthen the customer experience.
For this reason, ensuring the quality of information is paramount in data management for SMEs and all types of businesses. Accurate, up-to-date and unified data are valuable assets that increase business profitability in today's hyper-connected world.
Today, exploiting the advantages of data generated by on- and offline channels is imperative for companies to add value to their offerings. The 2019 State of Digitalization Survey published by Vodafone revealed that SMEs, microenterprises and freelancers had plenty of digital resources. Specifically: internet and device-to-device connectivity, 83% and 75%, respectively; collaboration platforms (79% and 60%), IoT through everyday devices (57% both). They also have cloud and hosting services (62% and 45%), websites and ecommerce (46% and 39%). To this we must add that, in several aspects, these percentages have increased due to the acceleration of digital transformation driven by Covid-19.
However, to carry out effective data management for SMEs it is essential to take into account the considerations that we summarize below.
Establishing a strategy: essential in data management for SMEs
Indeed, data management for SMEs and companies of all sizes requires an appropriate strategy. Only through an organized plan is it possible to successfully address the challenge of the 5 Vs of data: velocity, volume, variety, value and veracity. So establishing accurate policies and alignments will help to:
· Make data integration feasible.
· Avoid duplication, inconsistencies and redundancies in information.
· Increase performance when using data.
· Increase the reliability of the data for the accuracy of the analysis.
· Facilitate the making of appropriate decisions based on the data.
Accordingly, it is essential that this unique strategy includes very specific actions, among them:
Establish Data Governance
First, the enterprise must implement strong data governance. Data Governance defines the critical policies, procedures, technology, roles and responsible parties to define a single methodology for managing data assets. Therefore, those in charge of data governance must approve and communicate the guidelines, regulations, metrics and architecture applied to the processing of information. They must also monitor compliance with the guidelines and standards established in all areas and levels of the organization.
Specifying the data architecture
In essence, the data architecture comprises the development of the data management model. This includes the configuration of the data base, the storage and integration of the data, as well as the proposed architecture for the metadata. Necessarily, this process should anticipate alignment with third-party information processing models, such as suppliers, distributors and/or points of sale.
Ensuring data security
Today, data security is not limited to safeguarding information as a valuable corporate asset. It also involves safeguarding identity and data on customers and users, as established by the General Data Protection Regulation (GDPR). In this sense, guaranteeing data integrity and confidentiality is a priority that must be considered in the data management strategy for SMEs. In short, this concept encompasses all the actions necessary to preserve corporate data against threats of unauthorized access, queries and modifications.
Efficient management requires appropriate technology
We have said before that the digital transformation of companies goes beyond the incorporation of technology and involves changes in corporate culture. But, undoubtedly, data management involves the use of digital resources: network connectivity, infrastructure, hardware, CRM, ERP and even cloud computing, among others.
Similar to the digitization plan, the data management strategy for SMEs should consider the gradual incorporation of tools and solutions. All this allows to increase the capacity for the capture and processing of information. Therefore, it is important to anticipate such technology acquisitions to avoid a lag with respect to the established Data Governance and Data Management plan.
An essential task: integrating information
Specifically, this integration consists in the possibility of combining data from different sources in order to obtain a unified view of the information. For this purpose, solutions that enable the capture, cleansing, monitoring, adaptation and delivery of heterogeneous data in different formats are indispensable.
In itself, the idea is to achieve the convergence of data from supply chain, marketing, sales and administration into a central system. Including data captured on the website, apps and social networks. In addition, information from market research and other aspects inherent to the business, generated by consultants and even data from IoT sensors in physical stores. In this way, it is feasible to use the data as a whole and extract valuable information for decision making.
Maintaining quality: a must in data management for SMEs
In this context of data of different formats, characteristics and origins, how is it possible to ensure that the information acquires and maintains a standard of quality? To this end, in principle, it is necessary to avoid establishing information silos in the different departments within the company.
At the same time, in the treatment and management of information, it is critical to apply solutions capable of standardizing, deduplicating and enriching data. Through such technologies we can add value to the data in order to get the most out of it. This would consequently help us to increase efficiency, make informed decisions and strengthen the customer experience.
For this reason, ensuring the quality of information is paramount in data management for SMEs and all types of businesses. Accurate, up-to-date and unified data are valuable assets that increase business profitability in today's hyper-connected world.