The importance of high quality, clean data
Without quality and clean data any solution will not realise the key benefits and the implementation will be seriously undermined. Data quality must be assessed and managed in legacy or existing solutions by profiling it for cleansing and in the extraction, transformation and load (ETL) processes to enable successful data migrations. When loading data, it will often initially fail validations and these failures need to be understood and fed into data cleansing and preparation activities. When this is done well it enables organisations to drive value and insight from their investment in business process applications and technology.
Understanding what needs to change
As an organisation matures it becomes more and more necessary to align people, processes and procedures with the technology and data advancements. This is an area that can be forgotten if the digital or cloud transformation is too fixed on the technical implementation. All digital and cloud transformation programmes need to put equal focus on people and processes/procedures as they put on the technology and data. This blog addresses the core data-focused areas to consider in the move towards digital business solutions and cloud business applications:
- Source to target mapping
- Broadening platforms
Source to target mapping
Source to target mapping has moved from unstructured to being very structured. Where consistency and completeness are key. To ensure data is in the correct format and of the correct length and type, the target load file fields must be mapped to the source data. This mapping exercise highlights any required data transformations. It is crucial that the relationship between the data load files is understood when creating the files to be loaded. We recommend that you do not just focus on mandatory data required to ensure the technology will work but also ensure that data required by the business for their processes to work is also included.
It is important to always consider the wider use of data, both current and future, across an organisation and drive out consistency. With digital and cloud offerings becoming increasingly broad, traversing multiple business functions such as supply chain and back office, data can no longer be looked at in isolation within a particular function. The user experience needs to be consistently high and aligned across all the business functions. For example, in a retail business, it is not enough to simply consider supplier data from the perspective of finance, with purchase orders, invoices and payments, the data must also take account of buying and merchandising considerations such as factory locations and lead times.
The multiple use of data across functions makes it even more important to ensure the data is clean and correct and able to support diverse needs, whilst providing a single source of the truth. Data is more important than ever.
Whilst individual platforms are expanding in their functionality, there remains a need to integrate digital and cloud offerings with each other and with remaining legacy applications. Careful consideration needs to be taken with regards to the architectural road map and what applications will be remaining in the longer term. This then needs to feed into decisions on where data should be mastered and where it can be maintained and deleted/archived. It is also important to consider what is ‘good enough’ at this point in the steppingstones of that road map. Focus should be on best practice and strategic goals, utilising support from architects and data governance.
Cloud applications must be as close to the generic ‘out of the box’ as possible and strong resistance needs to be in place to prevent tailoring to old bad habits and ways of working. Data owners and data governance becomes key to ensuring data quality remains high and data continues to be consistent. The introduction of data standards, data naming conventions and data validations must be implemented with top-down support. Integrations also need to be thought through with a move away from specific one-off point to point coded solutions, to the use of generic integration tools.
Data not only remains a key ingredient for successful digital and cloud transformations, but it is taking a more central role as the glue that holds all the applications, within a business landscape, together. The use of data across multiple functions and the need to manage a single-governed best practice view is extremely important. The transformation does not need to be world class but does need to be good enough. This must add value and support the overall business goals in the context of the wider road map. Moreover, data governance needs to be implemented across an organisation and not just seen as part of a transformation programme, otherwise it will not be sustained.
It is also important to note change management is crucial for the success of digital and cloud transformations and the necessary focus on data and data governance. The team must be taken on the transformation journey so they can mature, and they alter their processes and procedures to fit with the more mature business, the technical transformation is enabling. Ultimately, a strong data governance function will only succeed if all have been on the journey and understand its importance. The effort required in this area should not be underestimated.
Get in touch with our team to learn more about digital and cloud transformations.