We at Dataception, evaluate the real time
fact on data and analytics use cases, features and functionalities that support
business needs, as well as underlying data management and governance
technologies that assist those use cases. We also checked the real time
implementation hurdles.
Out of our evaluation we think the data can
either be a boon or a curse!
The same asset- “data”- is holding back the
potential innovation and process automation.
Here is how and what is our frame work to
overcome the hurdles.
# Collection of Meaningful Data:
There is huge volume of data. Every single
transaction generates volume of data and the employees are often overwhelmed by
this and they hate data! There are various channels producing data in various
forms – structured and un-structured. To collate and create a meaningful data
set is posing big hurdle.
# Non-availability of Data Catalog:
The enterprise does not have a proper data
catalog. Meaning, there is no inventory of data assets within the enterprise.
This data catalog may help data analyst or the data scientist and other
stakeholders. They may collect, organize and segment, access and that will
assist overall data management. The absence of data catalog many enterprises
would struggle to identify the very sources of the data within their own
organisation, let alone where all the data stored.
# Data Security:
As the data is a digital asset, the
security holds major hurdle. The enterprise’s key focus while any data or IT
oriented initiative is “Data Security”. Breach of the security could
potentially expose massive amounts of information to cybercriminals. The
information – such as credit card data – health information, bank account
details and social security numbers are dubbed as “toxic data” due to its
ability to harm an enterprise if it falls into the wrong hands.
# Data Governance:
Enterprises should structure their data
governance with clear policies and processes. This will support data management
and analytics. Many enterprises face hurdles, such as, where and how long to
store data, who can access which data and how they can access it, how the data
is shared across the enterprise and how to destroy (expiry date to data) the
redundant information (records) that contain similar information.
# Process fragmentation
This process fragmentation causes
enterprise multiple other problems – from missed business opportunity and
innovation to increasing risk of security breaches. There are multiple reasons
and practices that resulting into this process fragmentation. This one hurdle
leads to many other issues like
*conflicting business definitions, *lack of operational clarity, *Inaccessible
data, *Higher chance of data loss, *Higher storage costs,*Duplication of work,
*Slower development and prototyping, *Increased security risks, and all the
above may lead to vicious circle of
existing process fragmentation will lead to even more complex process
fragmentation in future also.
# Lack of IT readiness
Our study shows that only 5.3% of
enterprises are only having vision on their IT policies and processes. Many of
them started their journey as early as 2017 yet they are not completed the
implementation in some parts of the enterprises. We are also surprised to note
that less than 1% are ready in health care sector. Where are the counter parts
in developed nation are implementing RPA and other robotic automation
implementation. The IT department s are not ready to create a vision on their
IT readiness towards data and analytics and automation.
# Lack of Clear Vision:
The leader of the enterprises and the
stakeholders of the data and analytics are yet to arrive at a vision that may
enable the operation and future of the enterprise. The New Normal is coming!
This hurdle poses many inter woven challenges as simple as decision on storage
of the data.
# Lack of skills of implement
Our study result shows that only 32% of
enterprises are confident about their skill set available to implement and
operate data and analytics along with process automation and artificial
intelligence. The rate of change in technology and approach towards process the
data poses a very tough challenge on skill set of the human resources. The
enterprises continue to invest on employee training and upskilling them to
remove this hurdle else they may join hands with service providers who may help
them to implement.
# Resistance to change
This hurdle is part of any enterprise who
are taking new initiative. Changing nature of customer demand, changing nature
of products, changing economies of production and changing economics of distribution
drive the enterprise to implement data and process oriented deep analytics and
automation. Whereas the resistance to change is the first and formidable
hurdle. In our study only 47% of business owners and CTO and COO believe that
they may overcome this hurdle. In health care industry it is only 36%.
# Cost to implement
Enterprises who are ready to adopt new
normal face this hurdle as they have no budget allocation towards this
initiative. The cost of implementation getting complex and higher when the time
it takes along with finding right service provider and commitment towards hand
holding all through the implementation process. Enterprises find this hurdle as
major one. However our study shows that lack of vision and skill availability
are resulting to this cost escalation and return on investment.
# Speed to implement
Enterprises need the implementation to be
completed in days. Where as in reality the speed is considered as myth! Only 12
% of enterprises are satisfied with their implementation speed. 88% expressed
their dissatisfaction and they are stuck with the service provider and IT
department. Selection of service
provider, the method and the tool are going to decide the speed.
We at Dataception are experienced to
overcome the hurdles.
The solution:
Next posting! :-)
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