REPL Group: Why businesses need data science to unlock productivity
Ten years ago, we thought of productivity purely in terms of inputs and outputs. However, as information becomes even cheaper to store, businesses are inevitably moving from lakes to oceans of data. Data science is the key here to helping them understand productivity by unlocking the detail in their data. Data science is being used to great effect within the online retail sector, as such, it’s high time businesses followed suit and begin to look at how they can use data to improve productivity.
What is data science?
Data science is about more than crunching big data sets. It’s a combination of smart analytics, machine learning and artificial intelligence that “bring data to life in a hypothesis-driven approach”. Within the retail sector, data is frequently being used to inform decision making. From forecasting stock, category trends and loyalty promotions to sending customers tailored vouchers aligned to their shopping habits. We’re also seeing the emergence of data science being used successfully in workforce management, which could also be beneficial within businesses more widely.
Gaining insights from data
The amount of data businesses have differs greatly, but where businesses do have relevant data, they often find themselves unable to leverage the true value of the information. Publicly available data, such as weather or traffic, for instance, could be combined with existing internal data to improve forecasting by identifying any potential external impacts on the business. With millions of rows of data available, a single spreadsheet is unable to capture the whole picture. Businesses therefore need to look for an alternative way to store and analyse data - and that’s where data science comes in.
SEE ALSO:
-
Flexential drives digital transformation through a robust and holistic data center infrastructure
-
The Magic Triangle of Data: Machine Learning, Automation and the Human Force Driving Data Science
Instead of splitting data across multiple spreadsheets, data science uses powerful computing technology to look for patterns across and throughout the data lake. This means analysis takes place using every piece of data the company has in its entirety. With millions of items of data in one place, data science will enable businesses to unlock new perspectives into productivity and generate real value from their data. In the retail sector we are seeing the effective use of data science within the following areas:
Workforce management
Without data science, retailers can end up with a lost opportunity: they may have too few staff members to cope with demand or could end up overstaffed. But add detailed, automated large-scale data analysis to the operational mix and leaders will understand exactly what’s happening and prescribe a data-driven solution. One example is to use data science to understand which employees work well together, based not on manager observations but by looking for patterns where pairings are most productive and offer the best levels of customer service. The system then uses this insight to create optimal schedules that control cost while maximising productivity and customer support. This is something other businesses could also benefit from, particularly in shift-work within call centres or in factories in the manufacturing industry, for example, or even when restructuring teams. It is also something that could benefit healthcare institutions with rostering, helping them to detect who works best at what time of day and alongside which individuals.
The pursuit of profit
Data science can also be used to solve broad problems, like profitability. By understanding which operational activities contribute to surpluses, it’s possible to build a performance management framework so business owners can focus on these areas. This is accomplished by reviewing the entire makeup and impact of a decision and interpreting historical data, like sales, profit and revenue, and then looking for links that might not necessarily be obvious. With deep learning and data analysis, data science can predict the outcomes of different decisions.
When the optimal decision is identified – one that will help maximise revenue and minimise cost – the result is presented to leaders. With the evidence to support the recommendation, data-driven decisions can be taken with confidence.
An exciting opportunity
Data science has outgrown the lab and now informs real-life applications and decision making. As we’ve seen from the retail sector, data science can do wonders for unlocking productivity and has helped retailers get the most from the staff by providing the intelligent insights that just can’t be gained without data science. With the development of integrated systems that will enhance collective thinking, it’s anyone’s guess where this powerful new technology could take us in the future.
As the power of data science becomes increasingly apparent, this presents an exciting opportunity for businesses to gain real value from their data and use it to further their business not only in terms of productivity but potentially also in terms of profitability. The sooner businesses begin to take advantage of this, the sooner they and their workforces will begin to reap the rewards.
