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In order to help attendees gain a clearer idea of what to expect at the AI & Big Data Leaders Summit Hong Kong 2019, we recently had an interview with Susan Poon, Global Head of Data and Analytics, Asia Pacific of Thyssenkrupp Elevator. Susan is responsible for supporting and enabling Elevator's Digital Transformation Strategy, aiming at building the competencies and practices of data governance and data management. 
 
In your opinion, does ‘agile organisation' necessarily meaning pursuing technology?
 
Agile organisation does not necessarily mean pursuing technology. It is rather a shift in how we organise ourselves to achieve the goals of the enterprise in comparison to the traditional hierarchy of the organisation design. There are many references available regarding this topic online with a formal methodology behind. However, in my opinion, it boils down to one sentence – self-organising based on purposes to achieve the intended business results in an agile way. How we go about doing it can vary from a full-scale enterprise transformation to starting within your own organisation by adopting the concept. I’m not a believer in “best practices” as every organization’s challenges and opportunities are different. Ultimately, we need to be clear on where we are going with a vision to rally the organisation around a set of goals which can inspire and motivate the teams. The degree of implementation depends on the level of change one can influence. Agile organisation requires more disciplined collaboration and empowerment for the model to work. This may not be applicable to all right at the get-go. Some might argue that you can achieve limited value if the agile organisation is only a subset of the enterprise. I would suggest focusing on where you can have a positive impact and where your team are ready to explore before taking on a significant transformation shifting the pendulum drastically.  
 
Source: Pixabay
 
What are your ideas for building data governance?
 
Everything that we do should centre around the business objectives and benefits which applies to build data governance as well.  A few questions for consideration – 
 
1. Why data governance? To start, be clear on why data governance is important and where it can truly add value.  Is it a statutory requirement? Where are our business challenges? What is the value of data for our organisation? Articulating the “why” helps to drive a consistent message and guiding principle for data governance.  
 
2. Who owns the data? Map out a clear blueprint on the data ownership depending on the organisation set up and enterprise goals. What is the reality of your organisation? Are you organised in an end-to-end process-based structure or a functional structure? This determines how you define the ownership of data. Since data flows through the entire organisation, data owners and stewards need to have the authority to ensure the entire flow is smooth across the organisation boundaries. 
 
3. What data to be governed? Link the associated data elements to be governed with the data owners. Not all data are equal in value and importance. Setting up a two-tier model which includes both a clear set of common enterprise-level goals to achieve and a certain degree of variation within the data domains per owner depending on the criticality to the business. 
 
4. How to govern the data? Determine the layers of data such as master data and transactional data by each area to determine the “good enough” line. Pursuing zero defect is always tempting but there can be a diminished return on an investment after a certain threshold. Having an adequate level of governance balanced with efficiency is always a challenge in any governance topic. 
 
5. Other consideration? Data governance as it stands alone has its limit. It should be tightly coupled with business processes to maximize its value. How to build integrated data governance and business process governance can further enhance the overall benefit.  
 
Here are the few questions that I would recommend mapping out to drive toward effective data governance. What can corporates strategies benefit from business intelligence and analytics tools? Business intelligence has been a decision support discipline in most organisations for many years. However, traditional BI tends to fall into the category of fixed dashboards and reporting. The modern and advanced business intelligence and analytics tools can enable the corporate strategy in a few ways:
 
  • Data-driven organisation – it’s important to enable the front-line employees and managers with the right data to make the right business decisions every hour of every day. By having the right information available at the fingertips of the right individuals shifts the discussions and decision-making to fact-based instead of anecdotal comments by the coffee machines. Having a data-driven organization also means a built-in mechanism to drive data quality at source. This will ensure a level of confidence and visibility from the field to the board room.
 
  • New opportunities – extending the analytics capabilities can potentially create or expand the market offering of the companies. Many organisations started to explore and develop machine learning and artificial intelligence as examples with varying degree of success. It will be important for corporates to consider how technology can play a role in enhancing current offers or creating new ones. Pursuing innovation requires some pragmatism to eventually industrialise and commercialise while allowing for failures within certain boundary.  
 
  • Re-engineering and optimising digitisation – connect analytics with the processes can help the organisation more efficiently revamp and optimise business operations. Data and analytics can be used to evaluate the efficiency of the existing processes beyond KPIs and zoom into specific transactional patterns. We should not box ourselves in a stereotypical or “industry defined” mindset. Focus on what can make a difference and strive for incremental and/or transformational shift leveraging analytics capabilities. Not many small and medium businesses plan to achieve digital transformation, regardless of customer expectation of responsive businesses. 
 
What is your advice for SMBs to leverage technology?
 
For any organisation small or large, having a clear business strategy is the cornerstone before embarking on any digital transformation. It’s easy to fall into the buzzword trap and lose sight of what matters to the company. Especially for SMBs, it will be helpful to be able to quickly sieve through the right opportunities to invest using design thinking concept. Prototyping business ideas to leverage technology doesn’t always have to start with technology. By taking on the concept prototype, SMBs can evaluate the expected business outcomes with a more educated simulation than just a hunch. With a few focused ideas, there are open source technologies with minimal investment available in the marketplace coupled with affordable cloud infrastructure. SMBs can turn their ideas into a feasible solution. The balancing vigilance is to ensure there is a certain level of consideration for information security and technology selection for longer-term scalability. There are certain advantages inherent for SMBs to adapt to changes with clear decision rights and nimbleness.  
 
Within the IT industry, what makes you most excited about right now?
 
The most exciting part of the IT industry now is the various components in technology are now coming together to enable more rapid development in the data and analytics space. The limiting factors such as storage cost, network speed, slow-to-scale infrastructure, high mobility data cost, etc. are all matured.
 
Susan is the speaker at the upcoming AI & Big Data Leaders Summit Hong Kong 2019. To find out more information about her presentation, please click here.
 
 

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