Modern organizational structure has made business easier through the grouping of various business functions into specific departments. This has made business operations much more effective. Yet, if one is not careful, the departmentalization can result in the isolation (another term for it: siloization) among different job divisions, when in actuality, these divisions are interdependent on each other.

This kind of siloization can also happen in data analysis, whereby data organized by internal departments are not analyzed in the context of other related fields. For instance, fi0ce, administration, human resources and marketing are closely related. Yet, oftentimes, at work, the departments cannot coordinate closely enough to make sure that their data could be presented consistently. As the quantity and diversity of data grows, silos tend to continue to grow as well, due to the disorganized way in which they are being analyzed. 

Therefore, with the advent of big data, which requires and promotes holistic understanding of how things work, companies need to inch closer toward a 360-degree understanding of their operations, as well as their data analysis. The holistic insight offered by data integration can mean discovering hidden business opportunities for the organizations as well as higher teamwork effectiveness (therefore cost efficiency). Meanwhile, data silos can mean lost opportunities, less effective teamwork and less cost efficiency.

Tracing the origins of data silos

While departmentalization comes in different degrees in different organizations, extreme forms of departmentalization (siloization) can happen over time due to several systemic organizational problems, according to an article published in Talend.com. 

One of them is organizational structure. Before the ever-versatile big data and cloud technology gained traction in modern business, different business departments had used to employ different methods to analyze data in their divisions based on their different needs. The different kinds of jargons used in different departments, along with departmental egos can also hamper understanding among them.

Finally, the different technology solutions used by different departments in accordance to their own needs can also increase the likelihood of data silo creation. Legacy systems in particular are not made for easy data sharing among different departments.

As a state-owned pharmacy company with many departments and branches throughout Indonesia, Kimia Farma also experiences similar constraints in terms of operational monitoring as well as solid and unify decision-making. As a result, companies find it difficult to develop their capabilities and compatibility, while on the one hand the company is required to increase value from their application and platform in order to meet customer needs.

How to prevent data silos (as best as you can)

Well, no system is perfect, so to say to you that perfect data integration can be achieved is basically just selling an unrealistic dream. Yet, what you can do in order to prevent data silos as best as you can, you have to first of all identify high-value opportunities according to your business needs. Then, make sure you pick the right data analysis methods that will serve these priority needs well. By investing on high priority needs which you need to work on to prevent data siloization, you can allocate your resources efficiently, according to a Harvard Business Review article.

Then, according to the same article, you need absolute support from the highest level of your company’s management, on the executive leadership across business departments and IT.

In the case of  Kimia Farma, the company finally took a step by using a data visualization platform provided by Telkom Indonesia, called Big Box. Big Box is an implementation solution from Telkom DWS for big data analysis to produce insight that is in accordance with the operational and business needs of the company, so that it can support the decision making, gover0ce, strategy and progress of the company. 

Big Box improves the suitability of decision making and operational monitoring, brings an overview of market analysis and public sentiment on products against competitors and the visualization of several branch offices with the local environment and community. In addition, Big Box also maps customer and product profiles, so the product promotion programs can match customers’ segments and generate prospects for marketing campaign activities. Moreover, Big Box has a role in increasing interaction and value from and with customers through enterprise applications or platforms, providing enhanced interactive monitoring that is now possible.

If you are looking to provide these solutions to your clients, who just like Kimia Farma, may be in need of any of these solutions, Telkom DWS is ready to provide you with the Big Box platform as a B2B service. 

By convincing the top management to get their blessing to invest in the best data analytics software to meet the urgent needs of your organization through data integration, you can sure boost its operational and cost efficiency. To see a demonstration of our plaform, get in touch with us through www.mycarrier.co.id