In the age of technology-led transformation, data is being generated each second through both man and machines. Despite knowing that data is one ring to rule them all in this digital age; most organisations fail to translate this thought into actions. Organisations are struggling in creating a data-driven ecosystem thus failing to utilise the true value of data for driving actions. One of the key challenges that organisations face is to manage or overcome the already existing data silos and to tackle this they try to tear this down and create a new data-driven ecosystem for the organisation.

In this blog, we will be learning about what are data silos, why are they bad, and how to overcome them.

What are data silos, and Why do They Matter?

Data Silos suggests the situations in which data exist in isolation. When data silos exist in an organisation that means, not everyone in the organisation has the access to the data. 

A.    How are data Silos Created? 

Some of the factors that leads to Data Silos in an organisation can be :

1.    Organisational Structure: The organisations have multi-layered departments and most of them are interrelated with each other. For example, sales and marketing, finance and sales, HR and Finance. Although the departments work together for achieving the common organisation level objective, their individual KPIs are different which leads to storage and usage of information in their own way, thus giving avenues to information silos being created.  Departmental separation causes the formation of information islands. In a large

organisation, data silos can easily be created because of the separation between many layers of management and the specialised nature of few staff members. In addition to this, the geographic spread of enterprises also adds to creation of data silos. 

A common example is a lead management lifecycle from identification to delivery. In most IT organizations, marketing generated interests are not captured on a common platform that is accessible for sales and management to monitor its progress, finance to forecast estimated revenues from the potential TCV, Delivery to plan in advance and do a skill gap analysis which can be leveraged by the HR department to leverage existing workforce and onboard people in a timely fashion if necessary.


2.    Organisational Culture: The enterprise mentality is one of the major reasons why data silos are formed in the first place. The reason for the creation of data silos is the absence of data exchange between departments. Many a times people don’t realise the value of having a seamless and transparent exchange of data which creates data silos. This lack of data interaction between the departments causes information duplicity and a lack of transparency within the organisation.

To enable the shift in breaking down inter department barriers and silos the initiative should be driven in a top down approach. There should be an intensive communication driven by the management showcasing their commitment to the cause and to generate confidence among the workforce. The messaging should be centred around understanding the problems with silos, the impact it creates on business and among their peers and the benefits of data sharing. 

3.    Technological: Due to the lack of interaction between various departments, there arises a chance of difference in technological usage. Data formats are different for different tools used by departments hence leading to a mismatch and misalignment of data capturing.

A member in the team uses multiple spreadsheets to record client data on their system, or departments subscribe to multiple vendors to manage and store their data but lacks integration with an organization-wide ERP or CRM tool. 

In order for companies to gain a competitive advantage it is imperative that democratization of data along with the necessary governance measures gets implemented. This will enable people and departments to navigate, analyse and interpret data at scale thus allowing a tectonic shift from reactive to proactive decision-making model. With technology innovations like data virtualization software, cloud storage and self-serve BI applications available at disposal, some progress has been made but there is scope for a larger awakening at the ground level of the working model. 

B.    Impact on Business Growth

The data silos in an organisation not only affects the storage capacity but the efficiency, productivity and business outcomes.

1.    Time is Money:  
According to Mckinsey, employees spend almost 1/5th of their average week searching and gathering information. This means every employee spends 8-10 hours every week to gather the required information. 

In an organisation of 100 people, assuming you pay an average of $10 an hour to your employees, the information collection would be costing you, 52*8*10*100 that is $416,000 annually. 

2.    Increasing storage cost: 
The data redundancy and duplicity are Costing you more money than you can imagine. The duplicity of the information is causing data inconsistency in the organisation. If your data is present at multiple places, there will be multiple copies that must be present, and the storage cost will be increasing manyfold. You can get infinite storage with your cloud provider but the data consistency and accuracy, that will create multiple sources of truths or in fact none. 
One such industry that can benefit from is the healthcare industry. With no centralized systems in place to capture, track and transfer, monitor health records, reports and related patient data that is hospital/location agnostic, each medical treatment facility resorts to filing enormous amounts of paperwork every time a new patient comes in. Thus a patient who may have visited a dentist, an ophthalmologist and a physiotherapist at separate locations in the city would have ended up sharing basic information every time separately which otherwise could have been secured, saved and retrieved from a single source.  

3.    Lack of a Collaborative environment: 
As every department uses its own data sets to make decisions, implement policies and create its own myopic vision based on its analysis. These things not only hurt the departments but mainly the organisation at a larger level. If your departments are not working towards achieving a common goal, you will not achieve what you envisage. The creation of data silos not only restricts the transparency in the organisation but also creates extreme competitiveness between the departments which were otherwise supposed to be working cohesively. 

4.    Failure in seeing the big picture:  
The data silos give you a distorted and incomplete view of your business operations. Data silos prevent you to from getting a 360-degree view of your business by limiting information and removing data authenticity. They just slow down your business growth and hamper you to achieve your true goal. 

C.    How to Overcome Data Silos? 

As we know by now, whether we like it or not data silos do exist in every organisation. But how do we avoid them, or overcome them? 
Illustrated below are techniques which were successfully adopted by companies for alleviating or controlling creation of data silos:

1)    Creating a more collaborative environment: 
Many a times people responsible for data generation and exchange are responsible to create these silos, an organisation can avoid them by creating a healthy and collaborative space. Different team members must understand the importance of sharing a common goal and work together to achieve it. Avenues should be made available for triggering this collaboration amongst employees.

2)    Using an integration platform: 
To avoid silos created due to technological barriers, organisations can look out for an integration platform. This integration platform will help you in identifying the instances of data being present and create a data pool that will be of high quality and enhanced accuracy. For organisations using cloud storage, an Integration platform as a service is the right path to get the desired solutions. 

3)    Clean and Create 
Organisations need to perform a data audit to remove discrepancies, clean the unwanted data instances, free the storage space, and create a single source of truth for others to make a data-driven decision. This in turn will create a data-driven ecosystem, which your organisation has been envisaging for a while.

4)    Creating an Enterprise Data Warehouse: 
A data warehouse is a large collection of your business data that helps you make data-driven decisions faster and accurately. Rather than creating connections across applications which will essentially be an expensive and arduous task, a better approach is an investment into Data Lake or Warehouse, where you only bring what’s essential for drawing insight. 

Organisations can get benefitted in many ways post data warehouse implementation. A data warehouse provides: 

a.    Enhanced Business Intelligence: By providing you the necessary data from various sources in a single platform, it empowers your decision-making by removing lack of transparency, a hindrance on business process performance, and helps you make decisions more intelligently. 

b.    Faster Operations: It helps you consolidate all the data from multiple sources into a single platform, hence searching and gathering information becomes faster than ever. It allows you to get the desired data with a single query and hence saves you time, effort, and money. 

c.    Enhanced data consistency and quality: Data warehouse conforms the data generated through myriad of platforms into consistent formats required for analysis of that data. By ensuring this conformity, it maintains the sanctity of data amongst the departments and hence providing a better and effective data quality.

d.    Interoperability with on-premises and cloud: Today’s data warehouses are created keeping in mind the private, public, and hybrid nature of the cloud services. Many data warehouses are 100% cloud-based and provide scalability and data security for your operations. 

e.    Competitive advantage: It helps you effectively strategize, operate, and evaluate your business performance based on the data available. It helps you by delivering greater and intelligent insights from the historical data available and enables your organisations to make informed decisions. It provides you smarter, metric-driven decisions at every step of your operations to gain an extreme competitive advantage. 

 

Conclusion:  

The silo struggle has been around for a while now and both humans and technologies are responsible for their existence. In this high-speed digital age, business success relies upon collaboration between humans and the real-time insights driven from the data. Organisations need an end-to-end data strategy in place if they want to move ahead with fast-paced growth. Enterprise Data Warehousing is one of the promising solutions that can easily help organisations to manage this Silo struggle and delivers a competitive edge in this ever-changing world. 

Companies need to include data strategy in their business strategy for effective business performance. In this world of digital transformation, many organisations need a partner or an expert which enables this technology-led transformation for the speedy, secured, and seamless transition of the business. 

About the Author:

Vikas Gupta heads business at Motherson Technology Services United Kingdom Limited. With more than two-decade experience in the UK region, he has proven success in leading and delivering Digital Transformation and Change management initiatives for customers across multiple industries in the region. With an expertise in business development, entrepreneurship, data analytics and digital transformation, he is instrumental in helping businesses to leverage existing knowledge into Business ideas thereby creating Value propositions for Existing clients and new customers.

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