Big data is a game-changer in the world of business. Many CEOs across different industries have been paying attention to this new technology landscape. While several organizations are already known for their impactful big data best practices, many are just starting this long journey.
As the big data ecosystem grows every year, it is important to understand some of the prerequisites that are critical in embracing big data and data-driven decision-making culture in an organization.
Big data is not a “Plug and Play” technology. It involves a number of managerial and technological steps that are critical for success. Like any other organizational technology, big data implementation requires the full endorsement of an organization’s senior management, finding the right talent, and introducing a measurement culture.
From the top on down
The lessons learned from implementation failures of enterprise-wide systems such as ERP, CRM and SCM in many large or mid-size organizations indicate that executive sponsorship is the starting point for such large-scale undertakings. Big data introduces a whole new decision-making culture to an organization that cannot happen overnight.
Depending on the history of the organization, this change management journey could be very long. Nevertheless, senior management can play an important role in this journey. The management must lead by example with a clear understanding of the huge impact of big data on the organization’s information sharing and decision-making culture.
The alignment of the organization’s strategy, operational visibility, and investments in big-data related technologies can only be materialized when senior management fully understands the scope and challenges of this process and makes it easy for employees and stakeholders to embrace it.
Data-driven culture transforms organizations from a reactive to a proactive mode of operations, and brings transparency, accountability and speedy decisions. Incorporating this culture is not feasible through a bottom-up approach.
It is unlikely that individual employees or even division managers can change the whole organization by being the main advocates and activists. This approach may in fact lead to isolated or disconnected data-driven initiatives in organizations. Therefore, senior management must be ready to bring these fundamental changes from the top.
Investment is critical
Another critical area of readiness is the investment required to adopt big data technologies. Long-term vision and the need to know the scope of implementation are important here.
Yet, the cost of big data technologies may not be as big as the name sounds. This is mainly because there is a major shift of burden from hardware to software requirements due to the parallel and distributed processing architecture of big data and the use of commodity machines in the process.
In addition, many big data technologies are open source, one of their several appealing features. While a solution such as Apache Hadoop is not necessarily a complete answer in the big data ecosystem, there are many other big data platforms and tools that are also open source. Organizations can take advantage of these opportunities to get started.
However, this does not mean organizations do not need anything in particular or even proprietary to meet their specific needs. In addition to a foundation such as Hadoop, organizations may need several specific analytical capabilities from the tools segment of the software market. Therefore, management’s role in the investment decision is to focus on the prioritization and allocation of their investments in the areas of hardware, software and human talent.
Analytics is a team effort and finding the right talent to address the different needs is a major challenge for organizations.
On one hand, the team needs individuals who have a strong knowledge of the big data ecosystem and understand algorithms and statistics. On the other hand, the team needs individuals who have strong domain knowledge and experience in the industry in which they are competing.
Best practices indicate that the co-existence of these two different types of talent better equips organizations to practice data-driven decision-making more responsibly and within constraints and government regulations. It also helps to generate more effective business decisions and actions for senior management to understand the business value of big data.
Measurement culture
Big data also brings with it a new measurement culture. Management must define or redefine the measurement framework that incorporates appropriate incentives to mobilize the management team, employees and other stakeholders.
The new challenge in this frontier is the high expectation for business agility.
To avoid latency in every step of an organization’s competition, measurements and incentives must reflect the appropriate speed at the operational level and the mechanisms to synchronize with the tactical and strategic directions of the organization at the corporate level.
Entering the world of big data is very tempting when looking at its potential. It offers great opportunities for those organizations that are lagging behind, looking for improvements in efficiency, or even for trying to maintain their leadership in their competition. Yet, regardless of their reasons for adopting a big data strategy, organizations must first be ready in the above-mentioned key areas, among other things.
Anteneh Ayanso is an associate professor of Information Systems at Brock University’s Goodman School of Business. He teaches and researches in the areas of data management, business analytics, electronic commerce, and electronic government. He can be contacted at (905) 688 5550 ext. 3498 or [email protected]
