According to Tech Pro Research, 70% of companies either have a digital transformation strategy in place or are working on one. A conscious effort is being made by organisations to transform their markets before they get disrupted by competitors further along the digital journey. They are preempting future changes with new business models and digitally enabled products and services, and whilst aspirations are there, experience shows that, in practice, the level of digital maturity is variable across sectors and businesses.
For many businesses the move to a digital future comes in two phases. Firstly gaining experience through digital business improvement: automating and transforming existing business processes by the use of digital technologies. Then building business intelligence systems: making use of real-time data to bring about business innovation, creating new digitally enabled products, services and platforms to drive revenue and open new markets.
In many of our customer engagements, the first challenge we have seen is for business leaders is to understand the “art of the possible” to separate the hype from the “achievable now” where short-term payback can be delivered to build digital confidence for future online product offerings.
To take these first successful steps, it’s necessary to build the digital dream team, bringing together digital leaders with business, technology and data expertise and align to deliver expected business outcomes. In many cases this means working with external digital transformation experts whose practical experience with the cloud, mobile, data and integration technologies is needed to deliver.
We have seen many successful established businesses, especially those with remote workforces handling their primary customer interactions, still burdened by manual processes and poor access to data in the field. Historically job management and data recording has either been paper-based or handled through first generation of hand-held data collection devices. Unfortunately these tend to result in the need for a substantial, expensive and inefficient back-office admin function to consolidate and transform data from site or customer visits and results in poor employee and customer experience.
The approach we are seeing being successful is to focus on data flows and to deploy the latest cloud and mobile technologies to develop smart, Android applications with real-time access via web-services and APIs to centrally held secure cloud data integrated tightly to existing legacy on-premise systems.
Digital business optimisation optimises the field worker experience often allowing more visits per day; provides real-time data from customer to field worker to head office improving business agility, better customer advocacy and higher net promoter scores and also eliminates back office manual processes improving data accuracy and delivering a short term payback purely on headcount savings.
Providing real-time access to data from customer to field to head office then allows the next phases of digital business innovation to be undertaken; the launch of new digital services or repositioning of the company as a digital service provider.
Managing data in modern cloud platforms makes it possible to gather data at scale with very low cost compared with traditional data warehousing platforms; have better control on security and access and free it from legacy silos. Organisations can then analyse and use this business intelligence to make faster and more accurate decisions, or offer more comprehensive data, results or insights for customers. As clients become more digitally mature we are seeing them launch new premium digital service offerings complementing their now more efficient operations with the provision of advanced data reporting services for their own customers.
Where do we go from here? Businesses are currently using less than 50% of the structured data they hold, and only 1% of unstructured data. It is apparent right now that businesses are searching for ways to best leverage their data, but don’t have the tools required to achieve that. There is a huge amount of hype around Artificial Intelligence but we are already seeing practical innovations using Machine Learning (a much better descriptor in our opinion). Machine Learning can empowerdata analysts, the primary data warehouse users, to build and run models using existing business intelligence tools and spreadsheets. This enables business decision making through predictive analytics across the organisation.
Machine learning applications are already becoming common in areas such as online retailing with product suggestion engines building on structured data. We are also seeing innovations in unstructured data such as video and image analysis. We have recently undertaken a successful proof of concept for automatic pest recognition through image analysis in a machine learning model and for another client looking to help them monetise existing image and video catalogues though automated tagging of meta-data with machine learning tools.
Developing consolidated data platforms through digital business optimisation and the launch of new digital services coupled with the ability to leverage machine learning in the future will help businesses rethink their practices and produce actionable insights. It won’t be a surprise to see digitally transformed organisations generating more than 35% of their revenues in the near future from new business models that are ‘digital’ and have data at their core.