Data value propositions are specific to industries as relevance is derived from trends and legislation. At D8A we recognize the value of work field expertise and deliver distinct solutions per industry such as data in design, regulatory frameworks and and new developments.
Data for Industry 4.0 and legislation
The manufacturing industry understands the value of good data, especially within the digital supply chain or Industry 4.0. Both rely on good data quality to have flawless data integrations, robotics for automated handling, production forecasting, real-time warehouse management, digital twins and predictive maintenance for machinery based on Industry Internet of Things (IIoT). Existing data points within manufacturing are often in place for the needs of a particular department, yet insufficient for other end users. Efficient supply chains will benefit from a common “data language”. This common language is often resolved through a central data lake. A central tooling solution by itself is not enough. Similar to physical supply chains, companies should think systematically, focus on end products, define standards and measurements, introduce quality controls, and constantly refine their approach across all phases of data gathering and analysis.
Digital supply chains have additional challenges: the upcoming legislation pressure and development of new data-driven products & services. This can encompass hardware products enriched with data, which will deliver an additional layer of complexity to manufacturing. Similar to new products that exist of data and/or insights only. Most companies rely on the data lake to build new products. Once these new products are sold they will touch upon ‘traditional’ supply chain functionalities. This means traditional systems will need to transform to a truly new data-driven environment enabling supply chain digitization and data product ambitions.
Data for new financial services
Within the financial sector, the data activities are relatively straightforward. Most companies have worked towards a 360 view of their clients. This is complex because companies have multiple data sources to build the customer view. And, as data-driven financial legislation is quite mature, banks, pension funds, insurers and even Fintechs have put considerable effort and investments to meet regulatory requirements, transforming into being proven in control of data from source to usage at all times. Including the continuous exchange, transfers, and integration of data with trusted partners. A more disruptive development is the rise of Fintech. They are designed to be a threat to, challenge, and eventually seize financial services providers by being more agile, serving an underserved segment or providing faster and/or better service, often based on data & analytics.
These developments require a constant investment into data requirements, by strengthening their (risk) approach with mature data capabilities. And through solid central data platforms to capture and share data.
All financial companies are now looking for ways to monetize this investment. This often starts with low hanging fruit, such as sharing dashboards with their customer base. Or reselling curated and enhanced 3rd party data. And now they are looking to extend this to be able to be flexible enough to meet the increasing dynamic in the financial landscape (e.g., through fast rise of payment platforms). The next wave will be building new products based on underutilized data, e.g., for micro finances or tap into new markets based on new insights.
Data for e-commerce and brand loyalty
Most developments within retail rely heavily on data. The steep rise of e-commerce requires good data quality for sales, order fulfilment and delivery. The need for data quality has been a strategic topic for years in traditional retail. With the rise of digital commerce, data quality increases its relevance. The more recent development is the upcoming ban of tracking cookies, as announced by big tech firms (Apple & Google). These 3rd party tracking cookies are decreasing track & tracing of relevant customers. This will and shall be resolved by 1st party cookies, i.e., data that customers are willingly sharing for a benefit. The upside of it is that brand loyalty will most likely increase, due to a direct connection from retailer to company. It also means that the relevance of good data quality needs to be embedded already in the design phase, starting as early as wire-framing. This will mean a totally new way (medium article) of working for designers and app & website developers. Another retail development is Metaverse, a virtual world where companies and consumers share experiences and interact in real-time within simulated (retail) scenarios. It would mean more data than ever being gathered on individual users. This will require privacy controls and consistent data quality.