Make data live up to its promise

Data is increasingly at the heart of every business – its growth in recent years has been meteoric.

This trend isn’t slowing down, especially since the pandemic has accelerated the digital transformation of many economic sectors. Digital offerings have leapfrogged seven years or more of progress in the past 19 months. This has proved advantageous as well. Meanwhile, 83% of data-driven businesses gained critical advantages during Covid, according to a YouGov survey. This sea change is forcing organisations around the world to rethink their data strategy.

The surge in digital assets, processes and uptake of technology means that more data is being amassed than at any point in history. Remarkably, most of humanity’s data ever created has occurred in the past few years. Harnessing it, making sense of it and deriving value and insight from data have never been more important. Yet organisations are only now waking up to its inherent business value.

“The growth in data is exponential. Businesses are now storing a lot more. Yet the value that they are getting from data is not tracking the volume that’s being produced. There is seemingly no correlation between volume and value. We call this gap the ‘great data tension’ and it is a big issue,” explains Karl Hampson, chief technology officer, data and AI at Kin + Carta.

“This is not a sustainable place to be. The way businesses organise themselves for data needs to change in order to make the most of the global economy’s digital evolution. We need a revolution in how we enable data across the enterprise.”

Today very few enterprises can say they are truly data- driven. Some progress has been made towards this goal, but there is a long way to go. Many more businesses have put in the foundations for a data-driven approach; for instance, adopting the cloud to allow an elastic scaling of their digital and data services, so they always work 24-7. This full-scale shift has taken a decade. Corporations have also cracked how to make the modern software stack work at scale, which is a huge achievement. Organisations
have invested in digital transformation but have yet to apply this approach to data at scale.

“Data has not yet seen this kind of transformational and ubiquitous progress. We can now manage the modern complex software stack to meet all the demands upon it; we need to be able to do the same with data. During the next decade we will really start to see a difference in how firms harness the power of data, realising its true value and releasing the data tension inherent in many organisations. The big question is what will it take for organisations to realise this is a necessity, not a ‘nice to have’? For some, Covid-19 definitely accelerated the need for data but one last final push is needed,” says Hampson.

The fact is businesses frequently struggle to generate data insights and actionable data. Data often sits in silos. If it is stored in a data lake, making sense of vast amounts of data is an issue. Data teams do not always focus on how data can be used for real business outcomes.

Hampson explains: “Often strategies and thinking are not joined up across the business when it comes to data. There may be some history around silos due to legacy systems or walled gardens as a result of mergers and acquisitions. It’s not a technology problem, it is an organisational and change management issue. And, frankly, a human mindset challenge.

“There needs to be renewed direction from the top of an organisation. There must be a new mandate. Reframing the data problem is an important approach.” 

Most corporations think of data as an asset; there is little incentive to package it, refine it, allocate value to it and share it with others as if it were a product. But this is changing. 

Cutting-edge businesses are starting to apply product thinking to data, treating key information with the same care and attention that would befit something that was sold to a customer. This involves investment in product development and quality assurance, as well as making sure it is useable and accessible.

Rob Wadsworth, director of enterprise data at Kin + Carta, says: “By applying product thinking to crucial data assets, leaders now ask ‘how do we generate value from this piece of data and what problems is it capable of solving?’ The aim is to make the outputs of these data products available in a very consistent and standardised way.”

UK supermarket chain Co-op used this methodology when looking at its freshly baked goods. Every day more than 2,000 stores were throwing away stale croissants, pastries and bread. They were baked in the morning but by the afternoon many products were unsaleable. If orders and baking volumes were not fine-tuned it created a lot of waste, loss of revenue and unhappy customers.

A team collated a data ecosystem on the cloud around this issue involving sales, demographics and data based on one store. An algorithm was developed to help determine what should be baked and when. The focus was on the end-user, the store-based employee and the actions they needed to take to minimise waste. Once perfected, the ecosystem was implemented across the supermarket chain. It delivered a return on investment within six months.

This product thinking was built end to end, with front-line store employees in mind. The concept involved starting small, fine-tuning the product and then scaling it up. By applying product thinking, the team demonstrated value. Return on investment was crucial. In this case, productised data had an owner, which was also governed and managed. This involved 80% people and processes, as well as 20% technology.

“Product thinking has incredible potential to solve real business problems. You can generate results and value quickly. It also involves incremental gains. Teams need to be agile to solve problems with data,” believes Wadsworth.

“We have to start having more conversations about where data can drive real value for enterprises. If you start having this kind of dialogue then ideas start to flow, new concepts emerge and then you can start testing them.”

The automotive and manufacturing sectors are already deploying some forms of product thinking to data, in order to optimise their production lines and supply chains. It can work well with the high-volume roll-out of physical products, optimising processes and the data associated with their delivery.

Applying product thinking to data has a lot of potential in helping businesses meet sustainability goals, where data is used to reduce energy consumption, carbon emissions and waste. 

Laura VerHulst, data scientist principal at Kin + Carta, says: “Companies often view data product creation as a set-it- and-forget-it exercise. What many fail to understand is that after data lands in the hands of business teams, those business teams then begin to ask more advanced questions which require more advanced data products. If an organisation hopes to be data-driven then it must treat data as a product that evolves alongside business needs.”

More than 85 utilities around the globe, serving over 100 million households and businesses, depend on Uplight’s digital solutions. The global company based in the US, which is a certified B Corporation, has an ambitious goal of reducing carbon emissions by more than 100 million metric tonnes and saving consumers more than US$10 billion on their energy bills in the coming years.

Uplight has created an open API that gives utilities their own data: data that is clean, easy to use and actionable. This allows utilities and their customers to manage their energy use effectively. It helps demand forecasting and managing peak demand, as well as reducing consumption within homes.

The API even allows utilities to remotely adjust thermostat settings when demand is forecast to exceed capacity, where participating households can save 15% on bills and reduce their carbon footprint.

• There is not enough actionable data being generated – this needs to change. We need a new narrative and organisational design around data in a post-digitalised world.

• Look at discrete, real-life business problems in your organisation that could be solved by applying data insights. Build a business case for their deployment. Start to apply product thinking to this data. Deploy trial and error, consider the ROI and what is really achievable. Develop a proof of concept.

• Think and invest in small case studies, develop the data as a product concept, then scale up when you’ve proved it works. Build interest around your organisation in the power of product thinking by showcasing successes, then build on these successes with further buy-in and investment.

This article originally appeared in Thread, Edition 1. Thread is Kin + Carta’s quarterly magazine that cuts through the complexity of digital transformation. Making sustainable change real, achievable and attainable.