https://ift.tt/3JRDqou A new mindset to succeed in the data economy of tomorrow Photo by Marvin Meyer on Unsplash Are you as shocked ...
A new mindset to succeed in the data economy of tomorrow
Are you as shocked as I am when reading the statistic below?
A staggering share of 97% data currently sits unused in organisations.
Indeed, 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.
The dawn of a new era 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.
Enterprise Data Collaboration: 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 arewaking 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 when 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
Seriously, 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 data privacy and compliance. 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 the output — an ad-hoc analysis, a dashboard, an analytical app , you name it — but also the scale and speed at which enterprises can operate on data. Like in soccer where not everyone should be 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 don’t be surprised if your overall gameplay doesn’t improve. The real challenge will be to empower all players to perform to the best of their abilities, because data is a team sport.
Data collaboration made easy for everyone: An emerging business opportunity?
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. A pain without a solution? Of course not! Let’s consider a few emerging business which made it their mission to tear down organisational hurdles to make collaboration the new norm.
While the past two pandemic years have put enterprise collaboration on a stress test, software tools like Mural , Miro and Figma have provided companies incredible remedy to port creative workshops and design sessions into the digital sphere where collaboration between people relegated to working from home. Catering to the specific challenges of working with data, software platforms Deepnote and detective.solutions are rethinking the way interdisciplinary data collaboration can be staged in organisational settings. The team around Deepnote offers a Jupyter-compatible, data science notebook environment for real-time collaboration on machine learning model development. While the former gears towards tech savvy personnel, detective.solutions offers a digital co-working canvas with no code access to big data. This is to help enterprise users of any background to master the collaboration- and communication-intensive phases of data-driven projects.
As it is the case for all innovation attempts, time will tell whether such platforms are here to stay. But one thing is clear: Data analytics projects, whether they are in their conceptual infancy or already deeply immersed in data and algorithms, count on businessmen and data workers to collaborate on data. Failing on this imperative reduces a company’s odds to make serious money from any data carefully made available over the last few years.
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/
What if data became everybody’s business? was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.
from Towards Data Science - Medium https://ift.tt/331sWCj
via RiYo Analytics
No comments