How to maximize the returns from your data
Do you want to get to know your customers better, make smarter decisions, increase sales, and reduce costs, using both internal company data and data from external sources? Then data should become an important asset of the company and, like any other asset, you need to work with it appropriately.
Data management is the implementation and monitoring of programs, and practices that control, protect, and increase the value of the data and information resources in the company. It is important to develop a corporate data model and to implement new technologies for integrating, storing data, as well as ensuring data security and quality.
Thus, in this article, we will observe the tips for increasing the returns from the data and how to advance the company’s data transformations.
Why is data important for business?
Data plays an essential role in the development of the business. Research by Gartner in 2020 shows that 54% of businesses prioritize data and analytics as the efficient tools of their strategies, while 34% of respondents consider improving the quality of customer service and developing new products as their main activity. These results clearly demonstrate that data is becoming an increasingly important element of business strategy.
Data literacy has become a critical skill for organizations striving to continually innovate amid growing volumes of information. Today more and more companies see data literacy as an essential mediator between generating ideas and bringing them to life. By learning the “data language”, sales managers, lawyers, marketers, and other categories of professionals who do not have specialized IT skills are able to constructively communicate with data specialists, conveying their ideas to them.
Getting the data right is a multi-layered process, from hiring professional technology specialists and talent management to the restructuring processes in the company. The faster the company’s team can collect, visualize, and analyze data, the faster it can take intelligent actions that will be beneficial to the work of the organization and its customers.
Data strategy must be consistent with the entire business strategy of the company, and be an integral part of it because it has already become the same asset of the organization as people and money.
A data strategy is not just a high-level vision, it must cover all critical areas of the data such as its quality, security, warehouse, model, and analytics. The business-linked data strategy is about long-term goals and actionable, overarching plans for realizing a company’s data-dependent competitive advantages and opportunities.
The information stored in the data demonstrates the effectiveness of the work of the company and helps it develop and implement the best business strategy. For example, by researching its data, a corporation can understand which advertisement should be shown to the relevant audience to achieve the maximum effect; which platforms provide the biggest amount of clicks to the company’s website, etc. Based on this information, the company can improve the search for the target audience.
Companies that want to get benefit from the data must first be mindful of the reasons and goals they follow, rather than mindlessly chase new technologies. It is important to understand what kind of data is in the company, analyze it, and know where it can be used in the future. Only then it is worth moving on to developing a strategy and solutions offered by IT companies.
Components of an excellent data strategy
A data strategy based on modern methods and IT standards comprises the following blocks:
- Mission – a brief definition of the meaning of the data department’s existence.
- Objectives – the directions of activity.
- Tasks – actions aimed at achieving goals.
- Tactics – special actions to complete tasks.
- KPI – indicators that allow the company to assess the achievement of tasks.
If there is no proper experience in implementing the data strategy within the company, then it is best to turn to third-party consultants who can advise complex options.
For instance, one of the popular IT platforms that is used by data specialists is the Pentaho platform. It has an optimized user interface, a wide range of functions for efficiently managing vast amounts of data, and built-in tools for visualizing data obtained during analysis. Additionally, the Pentaho Business Analytics solution analyzes and visualizes data on several parameters. Before the start of implementing the strategy, it is necessary to collect data about the current state of affairs, analyze it, and only after that synthesize goals and appropriate tactics for achieving them.
A good example of the tactic is the planned schedule of the work. The presence of executable schedules is almost one hundred percent guarantee that the strategy has been adopted and will be worked on. But this process must be controlled. As with any process, control here is based on KPIs. Reports should be prepared on a weekly basis, which allows the company to evaluate the effectiveness of solving the assigned tasks using the selected tactics. Reports, in fact, are the main tools for monitoring strategy execution.
Invest in new innovations
All new industrial revolutions are driven forward by innovations in automation and artificial intelligence. Today there are many plug-and-play solutions that can improve the speed of data processes, among which are:
- Amazon SageMaker
This fully managed service gives IT developers and data specialists the opportunity to quickly build, train, and deploy machine learning models. SageMaker controls the work of machine learning at every stage of the process to make it easier to develop high-quality models. Now with the help of SafeMaker, IT specialists can quickly load data, create new notebooks, navigate between stages, set up experiments, compare results, and deploy models to work in one place, which is beneficial for the efficiency of the company.
- Machine learning tools
Today’s innovative tools of machine learning can also automate such data processes as identification and solution of data quality issues, anonymization of data. They are powerful solutions for processing extensive amounts of data.
- Software Hadoop
Hadoop is a software project designed to efficiently process large datasets. Instead of one system for processing and storing data, Hadoop suggests using clusters for parallel analysis of huge amounts of information. The software contains many applications and engines that offer a variety of tools to handle analytical workloads, to use data sets in different formats and combinations. As a result, it can lead to a faster understanding of the data value.
- Local interpretable model-agnostic explanations (LIME)
LIME can interpret the predictions of ML algorithms. This new technique interacts with scikit-learn and supports explaining unit forecasts from a range of classifiers.
Data is a tool, the people are doing a business transformation
The company needs to understand that when working with data, a business can face a number of problems. First, it is the competence of the employees. The company must be ready to attract professional specialists and provide the necessary funding. Otherwise, the company can get an incorrect analysis or erroneous interpretation of the data, which will entail problems in the further building of the strategy.
When implementing projects related to business-linked data strategy, it is important to ensure cooperation between different departments of the organization. Team leaders need to explain why the data processes are strategically important for the company’s success in the market. In addition, the leaders must establish an efficient and comfortable interaction of departments within the company.
Employees may ask: “What data will improve the quality of my work?”. In turn, managers need to provide them with access to such data. That means all employees must use the maximum of the company’s data to ensure business profitability. This is a qualitative change in the principles of doing business. Data should become the centerpiece of innovation and the entire decision-making process, driving business growth, and improving business performance at all levels.
Make cultural change
Already formed organizations can not move to the new data model overnight. First, it is needed to recognize that this shift in the corporate paradigm is an ongoing process. It must begin with a full acceptance of the new strategy by the company leaders, followed by concrete actions on their part. Here are three factors that deserve the closest attention to make a cultural change.
- Improve employees’ competence in data use.
A recent study found that only a third of companies can effectively use the accumulated data in their decision-making process to improve business competitiveness, increase productivity, drive innovation, and leverage customer insights. The biggest reason is that the demand for experienced data scientists has quickly exceeded the available data professionals. Competence in the field of data must become one of the requirements for employees at all levels. It’s that simple: if you want data to influence decisions in the organization, people working in it must have the skills to use the data. That is, companies must define the concept of competence and its levels for the employees, how to evaluate and encourage this professional skill in the team members, how to take it into account when hiring new workers and how to identify its importance for professional growth.
- To appoint a leader.
In order to develop a new data culture, a company needs to go through significant changes in technology, organizational structure, and staff development. The organization can start by appointing a new senior management position that is a data leader or data chief (many successful agencies have already taken advantage of this opportunity). Companies should stop outsourcing data management only to IT professionals, including measures such as updating, deleting, and ensuring data compliance. It is recommended to appoint certain people who will be able to provide the strategic use of data at all levels of the organization, carrying out communication between IT and the business.
- Reconsider relationships with partners.
The company should review the partnership agreements. That is, the organization should re-evaluate the existing relationship with partners in terms of data that both parties share. It is needed to analyze what sources the company collects data from and how it will be used. To determine the value of the data has its positive effects: the more often information is used, the more valuable it is. Evaluation of data will affect the way information is stored, as well as the principles of its distribution, publication, and the possibility of its protection and destruction.
Efficiently dealing with the data processes has already become a core requirement to the employees in successful companies. As forward-looking business leaders understand that data is quickly becoming a strategic asset for future business growth. To make the mentioned tips a reality requires not only improving the technology and implementing new innovations in the business but also changes in the corporate culture of the company.