4 ways to use data and analytics on your innovation journey
There’s so much choice in today’s market. Finding new ways to differentiate your service and deliver a competitive advantage to stand out can be challenging. The standard advice is to drive innovation. But how can even more, change be beneficial in a year of severe disruption? How can you start the journey? And what tools are available to help?
CurrRapid innovation enables many businesses to stay ahead of change and stand out. Ent data and analytics can help you understand new market behaviours, respond accordingly and fine-tune services on the go. We have found that employees feel empowered to innovate and propose creative solutions more confidently when they can access the correct data at the right time and in the right ways.
I’ve witnessed this culture change, and other business leaders widely recognise the positive results. In a Harvard Business Review report, 91% of respondents agreed that adequate data and analytics strategies are essential. Strikingly, however, only 20 per cent rated their organisations as mature in this area.
Becoming data-driven isn’t a quick journey. At Microsoft, it involved breaking down data silos and making many other changes to how we worked. Our teams still find it helpful to continuously review and adjust their journey based on changing external and internal factors. But successful transformations start by getting the basics right and building out from there. I want to share four key ways you can use data to speed your journey to innovation.
- Get a single, holistic view of business performance to drive innovation
Data comes from many different sources, whether structured, semi-structured, or unstructured. So how can you best use all those data streams, repositories and silos to unlock insights and feed innovation?
By combining your data into a single view across your business.
Let me give an example. The industrial technology firm Smiths Group has five business divisions with different data strategies, systems and reporting – they have 800 applications across the business. Employees found that they had to manually extract data from many sources to get a holistic view across the organisation.
Business divisions and leaders can make better and more informed strategic decisions faster. So Smiths Group decided to consolidate multiple business divisions and data sources – including enterprise resource planning tools, finance systems, and SAP applications – into a Data Lake. Employees can now find the data and analytics they need. The company can now follow up with new operational, process and service innovation opportunities.
2. Improve and simplify decision making
Our experience as a transformation partner has shown that organisations with a robust data foundation also ensure their people can make informed decisions. A single data repository, secured by account-based permissions, enables and accelerates this.
At the City of Westminster, employees can gain a single view of residents’ data to help make better decisions faster. In addition, they can quickly draw on rich visualisations and information dashboards to help them innovate more personalised experiences.
A single data repository can help organisations respond quickly to external and internal changes. For example, Ricoh is leveraging data and analytics to access insights that deliver process improvements and enhance customer value. By connecting their factory to a single data view, they can easily track inventory across all stages of the production cycle. This means they can make process innovations to drive efficiency and competitiveness.
3. Disrupt business models with innovation
Wherever AI and machine learning disrupts business models, innovation can be found. For example, secure AI solutions can now analyse images, comprehend speech and make predictions using data. This opens up diverse innovation opportunities, from deploying and fine-tuning new omnichannel customer-purchase touchpoints to chatbot testing, analytics and optimisation.
I’m still in awe of how rapidly AI can learn from increasingly vast tracts of data. It lets us deeply understand our organisations and customers, uncover insights, and find new relationships and patterns at scale. Yet when we nurture a data and analytics culture, we enable our employees to drive innovation as part of their everyday practice.
Allowing AI and machine learning to take over manual tasks can let employees do more innovative or human-only work. For example, while customer service chatbots handle frequently asked questions, employees can focus on cultivating customer relationships.
4. Empower innovation for all employees
Our research suggests firms that gain the most from technology have also invested in skilling their people. It follows that leaders who build a culture of continuous learning in their data journey will be the ones who achieve the most success.
In a learning culture that embraces all employees, everyone understands how data and analytics can enhance their performance, creativity and power to innovate. One reason for this is that tech competence enriches every employee’s contribution. Data and analytics skills, for example, enable us to see how effectively we’re achieving our goals. They empower people to identify innovative ideas, put them into practice and increase productivity.