The Digital Transformation of companies
When we talk about Digital Transformation, most of the times people think that it is the use of new technologies within companies. But using this technology does not constitute a transformation in the company. Rather, this transformation is based on the new business strategy opportunities that arise from these new technologies. To adapt companies in order to get the highest potential from the technologies available to improve business processes.
In other words, the Digital Transformation is not based on the technology used (Big Data, IoT, Advanced Analytics or Artificial Intelligence), but on its use to achieve certain goals and business strategies.
As Manuel del Barrio (Head of Business Development at Decide Soluciones) explained in his interview in the event ‘Big Data To Action 2018’:
“The Digital Transformation is not only about using technology, but also about changing processes within the company, structuring the entire business concept based on data.”
Digital transformation is no longer an option
Today, the Digital Transformation has gone from being an option for improvement to becoming an absolute need. This is due to the increasing competitiveness in the market and the difficulty of differentiation from the competitors.
If you don’t take advantage of the opportunities that these technologies provide to improve the company’s processes, your tools and methods will become obsolete. And competitors will gain a competitive advantage from this ‘Digital Transformation’.
According to IDC, 66% of CEOs consider the ‘Digital Transformation’ to be a key part of the business plan. A transformation that can be implemented in the customer experience, in the operational processes and in the business plan.
In order to know the result of this implementation, a study by CA Technologies shows us that Spanish companies that have decided to transform their processes have increased their sales by 39%. Because in general terms, what this change seeks is:
- To improve decision making (base decisions on data)
- To automate processes (saving time, processes and tasks)
- To minimize costs (in processes, labor ones, etc.)
- To maximize process efficiency (achieve more with less)
Advanced Analytics and its role in the Digital Transformation
Advanced Analytical techniques are capable of achieving the above objectives. With data analysis, we can base business decisions we make on real information, not assumptions, instincts, or viewpoints. In this way, tools based on this technology can be implemented to automate and improve processes and minimize costs.
On the one hand, Descriptive Analytics through historical data shows us what has happened in a company and why. Giving us a general picture of what is happening in the company in a simple and easy to understand way.
After that, Predictive Analytics allows us to transform these descriptive metrics into a set of predictions and very precise trends that will tell us what will happen in the company in the future.
Many companies stay here in the process of implementing Advanced Analytics, and use those future predictions to make their decisions. But these techniques have much more to offer.
If Prescriptive Analytics is applied to these predictions, we can identify the most optimal decisions taking into account the large volumes of data and the infinite variables and constraints. And thus automate the decision-making process. This type of analytics uses intelligence and processing skills to make proposals, evaluate all possible options and finally select the most suitable one in search of maximum performance.
An example of how Advanced Analytics can be used to transform processes
One of the sectors in which Advanced Analytics is being used most is the retail sector. These techniques offer a wide range of possibilities to retailers who can use them in areas as diverse as in-store product distribution, personalised shopping experience, stock management or intelligent workforce scheduling.
For example, workforce scheduling in the retail sector has always been a headache and a considerable time investment for store managers. Planning by hand or with a spreadsheet is a complex task and the result will not include all the variables and constraints that influence the process.
But if Advanced Analytics is used, Predictive Analytics will use the store’s historical data about customer visits to precisely predict the number of people that will come into the store at each time of the day, each day of the week, and each day of the month.
And the Prescriptive Analytics, thanks to this forecast and taking into account more variables (the profile of each employee, their sales and productivity by hours, their hourly availability, the tasks to be carried out or the applicable legal restrictions), will automatically generate an optimal sizing of the store at any time depending on the number of visits from customers, and an optimized workforce scheduling. This scheduling plan based on Advanced Analytics techniques will always seek the best option according to the following objectives: customer satisfaction, employee satisfaction and maximum store profitability (increased conversion rate).
This means that managers will always have the right number of employees in the store (no more, no less) and the right worker at the right time in the right place to serve the customer. Without worrying about constantly creating and changing the schedules and shifts of employees, thus having more time for other tasks of vital importance to the business.
In short, this example shows an improvement in decision making based on data, the automation of the planning process and the increase in the profitability of processes and, consequently, of the store.