1. Why businesses should not be intimidated by data
governance
By Staff Writer 15 April 2015 | Categories: Software
0
COMMENT
By AntionetteVan Zyl,SeniorSolution Manager:Data ManagementatSAS
Market forces are driving data awareness as businesses realise that they can derive significant value
from effectively analysing data and applying the findings to decisions and actions, and as regulators
tighten rules around how data should be managed.
‘Big data’ is still used as a buzzword in business. But data has always been available – it’s just
evolving as more data sources become available, such as cloud, mobile and click-stream data. And
with the growth of machine-to-machine technology and the Internet of Things, even more data
sources will come online soon. So how do we manage these new data types?
Proper data management starts with a solid understanding of data governance. Businesses also need
strong policies that enforce rules regarding data management. Effective data governance involves
people, processes and technology to ensure consistent and proper handling of data. It involves all

2. levels of data processing, including data management, data quality, policy management, business
process management and risk management.
Data should be clearly defined, secure and fit for purpose if a business wants to derive benefit from it.
To achieve this level of data reliability, policies should specify how data should be captured. This
quality control measure ensures that any data issues are corrected at the source and that information
assets are formally managed throughout the enterprise.
Effective data governance practices require support from executive management if they are to be
successful. However, many CEOs do not link data to business value, believing that data is an IT issue,
while IT believes it merely supplies the data to the organisation.
Another challenge when implementing data governance strategies is that different departments within
an organisation have different agendas when it comes to data. As a result, they may each have their
own processes for managing data, resulting in siloed systems that don’t communicate with each other
and are difficult to integrate.
There is a perception that data governance is a massive and intimidating task. Businesses know they
should be doing it but they don’t know where to start. Data governance doesn’t need to be applied to
the entire organisation in one fell swoop. Rather, when embarking on the data governance journey,
businesses should start small – in a single department. Data governance requires change – change in
mindsets and change in processes. It’s much easier to convince staff and executives of the business
value of data governance if benefits can be shown in a single area and expanded from there.
Data governance framework
So where do you start? Below, I have outlined a top-down data governance framework that will assist
any business in establishing a single, consistent set of policies and processes for managing data. The
good news is that data governance is not a linear process – businesses can start from the top, the
bottom, or somewhere in the middle. My advice is to start with those areas that are already in place
and work from there.
Plan
Determine the business’ data governance readiness. Identify current high-impact projects and
upcoming initiatives and link these to a strategic initiative. For example, one business strategy could
be to increase customer retention numbers through a loyalty programme and setting up social
platforms to engage with customers. Initiatives to achieve this could include using analytics to
anticipate customer need based on behaviour trends and to tailor offers and communication to those
needs.
Next, assemble a core working team that will provide oversight, manage risk and assess compliance.
This group of visionaries will define the data governance charter, including the business mission, key
benefits and guiding principles.
Design
Identify an initial target project, such as a customer loyalty programme. A data governance council is
decided at this stage, which will serve as the main decision-making body on the project. It will also
determine the decision rights, list key decisions, engage other decision-making bodies and assign
accountabilities.
It’s important at this stage to refine and formalise data management – this is where IT will be roped
in.
Execute

3. Go forth and launch your data governance process! Key to ongoing success is to continually measure
and refine the process, monitor progress and report issues or risks. At this stage, data governance
should be absorbed into the software development lifecycle so that it forms part of all processes going
forward.
Poor data governance can cause many headaches for businesses, including poor customer service,
limited upsell/cross-sell opportunities, an inefficient supply chain, an inability to automate key
processes, poor operational planning and execution, and, importantly, exposure to fraud and other
risk.
On the other hand, efficient data governance systems present a single platform on which all different
roles and departments can be supported, allowing for the enforcement of central policies and
monitoring of those policies. As a result, information is treated as a business asset and is readily
available to support evidence-based decision-making – this saves time as the business knows the data
can be trusted and does not need to be verified.
Ultimately, the business is able to make decisions faster, its information is consistent and aligns with
values and goals, and risk management is improved – all because of collaboration and clean, valuable
data.
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