A staggering share of 97% data currently sits unused in organisations.
It is true, not all data is meant for analysis. Companies pool data for record keeping and regulatory compliance. But 97%, really? [1]. While the business benefits of leveraging ever-increasing portions of available enterprise data are out of the question, the one question we really have to ask ourselves is whether we are in a position where we could potentially do more.
A time after collecting data at scale
Technological advancements in big data made it possible for companies to collect, store and process data at unprecedented scale. “Data is the new oil” means to say that raw data, just like crude oil, isn’t valuable in and of itself, but, rather, the value is created when gathered and connected to other relevant data. But what does it help if we turn oil into petroleum but have not enough people to drive the cars we fueled?
We have reached a point where our ability to collect data exceeds the throughout at which we can analyze and act upon the data available to us.
In the data economy of tomorrow, success is no longer measured by the amount of data you have, but by the amount of people that are empowered to make use of it. To be successful, companies must shift gears from acquiring the right set of technologies to collect and process large amounts of enterprise data to empowering entire workforces to collaborate on the data made available to them. Those enterprises which fail to broaden the scope of who is empowered to work with data will miss out.
A bumpy road ahead of us
A large-scale data literacy study conducted by Qlik & Accenture finds that 67% of the global workforce have access to business intelligence tools, while 75% percent have access to data analytics software [2]. Enterprises are waking up the opportunity of enabling more employees to take advantage of data in their work. Clearly a leap in the right direction but one that leaves many of us stumbling. The very same study finds that increasing investments in data analytics & BI tooling have done little in enabling people to become more confident in working with data.
74% of employees report feeling overwhelmed or unhappy working with data
59% of employees globally exhibit symptoms of burnout (feelings of being unproductive, frustrated or stressed) when working with data analytics and business intelligence tools
36% of overwhelmed employees globally report spending at least one hour a week procrastinating over data-related tasks
14% percent would avoid the task entirely
What is going on? Simply put, technological advances have outpaced people's ability to cope. Providing people access to data in solitude is a stressful experience because data in itself is unhandy and, without additional context, well, just data.
Whatever technology stack we might be able to get our hands on, turning data into insight most probably always remains an interdisciplinary exercise which draws on diverse skills and knowhow spread over many heads in an organization. More often than never, the person who knows how to analyze data is not the person who has the context and business acumen to judge its rightfulness and relevance. Completely different people will know where to locate this data in the backend. Others will have to chip in when it comes to GDPR. The long list continues.
And while collaboration is key to success, organizations struggle to make it happen. A recent study by HBR qualifies organizational silos as the number one organizational barrier for organizations to transform into data-driven enterprises [3]. According to Statista, employees report a lack of organizational alignment as biggest challenge to big data adoption [4].
Eventually, the best technology is useless if users cannot work it. At the same time, great talent can’t be brought to bearing if the tools in use do not gear towards collaboration. The opportunity costs of carrying on the way things are right now are tremendous.
The moment data becomes everybody’s business
Nearly all employees are now expected to be able to use data in their roles.
In the current reality, data exploration is in the hands of a small group of specialists crunching data on everybody else’s behalf while most employees have to watch from the side-line until their analytical demands are being served. In this largely transactional setup, the confidence with which employees rely on data, the speed with which analytical requests are executed and the number of analytical requests that can be served at any given point in time are strictly dependent on the number of specialists available.
In an alternative reality, people of any background collaborate and converse about data. The moment data becomes everybody’s business, these metrics are set to skyrocket. Interdisciplinary dialogue between various business and IT stakeholders surfaces the necessary context for data to be understood and trusted. Making it feasible for different profiles to contribute knowhow would not only raise the quality of any output – an ad-hoc analysis, a dashboard, an analytical app - but also the scale and speed at which enterprises can operate on data.
Like soccer where not everyone is a striker, not everyone needs to deploy code and build complex models in a data-driven project. But to get to this point, all players need to communicate and collaborate to get the ball across the pitch. If you manage to find more strikers, great. But the real challenge will be to empower all players to perform to the best of their abilities, because data is a team sport.
The detective platform: Data collaboration made easy for everyone
Companies amassed a lot of data and tools to analyze it. With the human part of the equation left behind, these investments do not pay off today. Data Analytics projects count on businessmen and data workers to collaborate on data. Failing on this imperative kills your prospects to make serious money from the data companies managed to make available over the last few years. We created the detective platform to offer companies an immediate way out. How? By endorsing multi-user collaboration on an unbounded digital canvas with no code access to big data.
With the help of this platform, we aim to help enterprise users master the collaboration- and communication-intensive phases of data-driven project in time, in quality and with ease. Recalling the analogy of playing soccer, think of it as the perfect pitch for everyone of us to get the ball rolling J Want to learn more about the detective platform? Sign up to our newsletter and schedule a demo with us today.
References
[1] AWS Executive Insights (2018) - The Power of the Data-Driven Enterprise - https://aws.amazon.com/executive-insights/content/the-power-of-the-data-driven-enterprise/
[2] Accenture & Qlik (2020) - The Human Impact of Data Litracy - https://www.accenture.com/_acnmedia/PDF-118/Accenture-The-Human-Impact-Data-Literacy.pdf#zoom=50
[3] HBR (2018) - An infliction point for the data-driven enterprise - https://hbr.org/sponsored/2018/11/an-inflection-point-for-the-data-driven-enterprise
[4] Statista (2019) - Biggest challenges to big data adoption among corporations in the United States and worldwide, as of 2019 -https://www.statista.com/statistics/742983/worldwide-survey-corporate-big-data-adoption-barriers/