To this day, many organisations are still predominantly relying on manual operations. As the business world gets better insight into the role of data as an enabler, though, modern strategies are leveraging data to serve customers in an efficient and impactful way.
Abbi Agana, Director of Business and Innovation at Octavia – a leader in the affordable housing sector – describes her approach to combining business and data strategy within her organisation.
Planting Seeds for a Successful Strategy
Abbi emphasises the importance of creating a compelling story for data and how it aligns with business objectives. In the early stages of modernisation, you should consider the following points:
- What matters to the client: Your primary focus should be on clarifying how data can help the business’ bottom line
- Real-life case studies: You should present tangible examples of areas of improvement and proceed to show how data can provide actionable help
- Leveraging internal call centre data: A thorough and continuous exchange of information is key to an effective data-capturing strategy
- Holistic view or organisational information flows: The silo model is often a root cause of customer dissatisfaction. For this reason, transitioning towards a holistic and customer-driven approach can increase your opportunities for both higher performance and deliver
Creating a Data Community
According to Agana, your business strategy should be developed in tandem with a data strategy from the very inception. In her view, the data modernisation program is an accelerator:
The above process presents four strands:
- People: Optimising employee value proposition is paramount, as is ensuring your workforce has the right skills and is data-savvy
- IT modernisation: More often than not, the problem within an organisation lies in a lack of architecture and an abundance of legacy systems. This further emphasises the importance of assessing every organisational process in tandem
- Delivering value: You should observe the entire operating model to get a sense of how they deliver volume
- Data transformation: Once the above points are covered, you are now ready to begin the transformation
At Octavia, the modernisation strategy places the business strategy as a vehicle and the data strategy as a fuel:
Leveraging data strategically can give you a better insight into your clients, their trends, and their expectations. Creating a clear picture of the target audience ensures that those demands are met.
For data to stay on top of the client’s emerging needs, both the business and the operating model need to be optimised by it. Furthermore, your data structure needs to be resilient.
The First Steps to Data Governance and Data Quality Management
According to Abbi, governance and data quality management needs to be composed of the following:
- An intelligent data hub covering governance, enrichment, and survivorship
- A data information centre of excellence dedicated to analysis, science, and modelling
- Data ownership & stewardship
- Data quality framework
The democratisation of data is an essential step of the modernisation process. It is important to ensure that relevant teams within your organisation are able to manage and leverage data effectively:
- Operational use of real-time data: Data strategy underpins the business strategy, meaning business-critical data is key to individuals doing their jobs
- Staff roles incorporate stewardship: Regardless of the staff’s level of expertise, stewardship can be fostered by capturing, collating, or recording data
- “Measure what matters”: Performance indicators are inevitably linked to data
Data Strategy drives operational resilience and strategic agility
Abbi finds that, when combined with clean and accessible data, senior-level data ownership can be extremely empowering. This is because data is no longer subject to rear-view reporting, but rather embedded in the work and processes of your teams. As a result, your company is now strategically agile and responsive.
Through data stewardship and automation across all operations, the workforce is relieved of low-value tasks and offered access to real-time, quality-assured data enabling it to be operationally resilient.
Three short-term actions to take
Abbi found herself in the favourable position of modernising a data and business strategy from scratch. Notwithstanding, she believes that – regardless of where you are in your journey – there are three fundamental short-term actions you should take:
- Aligning data strategy with business strategy
- Undertaking a point of view (POV) that demonstrates how data can solve business problems
- Establishing a data community within the business
Common Pitfalls in the Journey towards Modernisation
Once again, Agana stresses the importance of highlighting the benefits of leveraging data to improve customer satisfaction. At times, you might find some resistance as this is a relatively new approach.
In the first stages of data strategy rollout, the data team will do most of the heavy lifting. It is your team’s job to coach other departments to enable them to be more independent in the long run. To this aim, performance metrics and data democratisation become all the more crucial.
Abbi on the key differences between governance and strategy:
Governance is more centred around framework and establishing discipline in relation to data quality, whereas strategy leverages data in alignment with the business strategy
How governance and data interact:
Strategy answers the question as to why you need governance, while data should be kept clean and managed. Notwithstanding, both elements should be modernised in tandem
How to onboard a business and gain its trust in the data strategy:
It will be necessary to provide bespoken training around the importance of data and data stewardship
Following the presentation, participas participated in the group discussions, and came up with some key learnings:
- For a data strategy to be successful, it will be necessary to operationalise data in function of client satisfaction, ROI, and overall business outcomes
- Deriving end-to-end value is what drives business outcomes
- Democratising data in larger organisations can be challenging, making it necessary to pinpoint and assign specific tasks to each individual team
- Individual teams need to be supervised holistically from the top so as to ensure smooth management of all operations
Data Leaders members can access the full interview and further discuss it with their peers. Interested in becoming a member? Get in touch.