My customer experience
A couple of years back, I met with an accident when driving my car and the vehicle, which was from one of the main automobile companies in India had to be completely junked. The insurance for the car was also done through a subsidiary of the same company. I had to go to the same branch where I bought the car to fill-up my insurance claims for the junked car. Still, I continued getting calls reminding me of periodic maintenance for more than a year after that. I even considered buying a new car with the same company but ended up purchasing a model of another leading automobile manufacturer. After a few months, when the insurance of the old car expired I kept getting calls repeatedly for renewal of insurance. This went on for almost a year. When I asked the caller as to why they keep calling me repeatedly despite my explaining every time that the car is no longer with me, the marketing person would always answer that my name was on the list.
Within a few weeks of purchasing the new car, much to my irritation, I was bombarded messages by the second company about exchanging the (new) car with the latest model!
This is a classic example of each department in a big enterprise having data in silos. If this is the situation in some of the leading enterprises, you can imagine what is the condition of the smaller companies.
This led me to think about the IT systems in enterprises. This is common in most of the companies and even non-commercial organizations. The CEOs and CIOs have to examine their IT systems and their policies and check whether any data silos exist in their organizations which comes in the way of the effectiveness and productivity of the employees. This is one of the easiest ways to increase the bottom line.
Data Silos
Data silo is defined as a repository of data under the control of one department or a business unit in an organization or an isolated point in a system which is segregated from the overall IT architecture of the system. The word silo originated from agriculture. The word silo meant a vertical tall structure used to store the harvested grains for safe storage and segregated from other silos so that a pest attack in one silo does not affect other silos.
Sometimes, a department may deliberately withhold information from the rest of the organization. Mergers and acquisitions also create silos. Plans made by the senior management in a siloed environment is inadequate due to the lack of holistic view. The data which could be used for improvement is buried and inaccessible.
Though data silos and information silos are sometimes used interchangeably, data silos are due to different technologies that make collaboration difficult and information silos are actually the silos created by knowledge workers intentionally to avoid sharing data with others.
Effect of data silos: Though each data is valuable for the department, the combining of the data could have compounding benefits. Data not shared is data not used to its full potential.
Data silos also reduce data integrity. Multiple versions of similar data waste a lot of effort and also creates doubt about which silo is up to date. Data silos also create additional storage costs. It also generates bad customer experience like in the example I gave at the beginning.
Advantage of breaking the silos: Data is the new “oil” in an enterprise today and breaking the data silo leads to digital transformation. Breaking the silos could result in sharing of data across the organization that gives the management a better insight and a 360-degree view of the customer, resulting in a competitive advantage. The senior management will certainly get a better idea of the big picture. Enterprises could automate the processes and reduce costs in different areas. The modern techniques of data analytics, artificial intelligence (AI) and machine learning (ML) could be used fruitfully to innovate, reduce costs, reduce labor by automation and increase profits. The financial institutions benefit by having better fraud prevention capabilities due to the breakdown of data silos.
How to break the data silos
Identification of silos
The first step is to identify the points in the system where data silos exist. Such points have to be connected to make them communicate with each other. The task involved is not just IT, but also bringing a more collaborative work atmosphere.
Identify who would lead the effort
The first step may require the appointment of a Chief Data Officer who will interact with the various business units, deal with the internal politics and bring them on the same page. He has to question the status quo, find how data is used and find ways to increase teamwork and collaboration.
Segregation of systems
Though the boundaries between different units cannot be removed in all cases, the boundary itself could be made flexible. The legacy systems which cannot be integrated into the new system have to be identified and replaced immediately. This requires a lot of time and effort and is certainly not easy. Data warehousing must be done and all the data has to be integrated.
Set up the new system
It is very difficult to make the data from disparate systems work together, but modern technologies could be used to make it easier. An intelligent system could be set up using automation which communicates to the various data sources with differently structured data and makes sense of it and enables the use of big data.
Build the process for future
Standard procedures should be established for collecting and storing data. Manual processes should be eliminated and all data entry points should be automated. This enables the top management to have a complete real-time view of the business at any point of time as there is no latency in the information.
Now the data is standardized, the standard procedure for collecting data will enable the use of big data analytics, AI and ML to get insights. The start-ups have a big advantage compared to the large enterprises since they are built with big data analytics as to the foundation of the business. It is not easy for big enterprises with their legacy systems and processes to compete with startups who are more agile. An example is the leading online retailers like Flipkart and Amazon who have state of the art IT systems with data up to date to the minute and accessible across the departments. They are able to analyze the information and get insights which help them to streamline their operations, increase their business, reduce their costs and use predictive analytics to target customers.
The result will be a converged infrastructure which can lead to digital transformation. Organizations, particularly the small ones can use cloud storage to store and share information, backup and archiving seamlessly across the departments and reduce the latency to access real-time information.
