Today, many companies love to talk about change, and those that aim to implement it in practice are starting to grow, day by day. And here come data-driven strategies to accompany this revolution, with the goal of achieving business objectives. Below, we explain specifically how a data-driven approach can improve a company’s future, optimizing decision-making processes through digital innovation strategies.
Data driven strategies: data culture
Data: a valuable asset for companies, which are increasingly certain that their use can determine business success. But how are data-driven strategies supporting the growth of business? The research conducted by IDC, in collaboration with Salesforce and Tableau, aims to provide an in-depth analysis, starting with the identification of three types of attitudes that differentiate the data-driven strategies of companies. On one hand, companies aim to increase sales, while on the other, they focus on customer loyalty and maintaining long-term relationships, without overlooking the improvement of process automation. This is where making data accessible to companies becomes a crucial step, allowing them to optimize digital transformation and innovation strategies. The value of technological investments also, and above all, depends on the recognition of analytics and their ability to guide daily operational decisions: making data accessible and usable by a broader audience of users promotes the improvement of operational and decision-making processes, creating new opportunities.
Data driven strategies: types of attitudes
Being a data-driven company today, as we have already discussed in a previous article dedicated to the topic, means putting oneself in a position to trust and rely on data and its inherent ability to drive the decisions that every company faces on a daily basis.
Implementing data-driven strategies today requires a balance between strategy and tactics, which in the long run can only represent the right combination for growth. The fusion of organizational and conservative and/or transformative models gives rise to three types of attitudes that differentiate business data-driven strategies:
Strategic change: For 28% of companies, data-driven transformation is managed with a strategy of integration and collaboration at the company level, addressing both organizational and cultural change.
Tactical change: 35% of companies manage data-driven transformation with collaboration across different business functions, addressing change exclusively on an organizational level.
Reactive change: 37% of companies experience data-driven transformation as a necessary reaction to market changes, maintaining the status quo with occasional collaboration mechanisms.
Companies with a strategic approach promote continuous process change based on data and consider the easy accessibility of insights and ease of use a fundamental element (84% compared to 35% of companies with a reactive approach). Tactical and, especially, reactive approaches lack a data-driven strategy that includes platforms, data governance plans, and industrialization of analytics (respectively 60% and 35% compared to 82% of companies demonstrating a strategic approach). Companies with a strategic approach offer “unlocked” data usage, meaning without special know-how to make it easily understandable to the broader audience, which is essential for implementing successful strategies as it allows each function to access data more quickly for analysis, addressing complex problems more effectively.
Data driven strategies: advanced/predictive analytics and CRM/customer analytics
In the not-too-distant future, the success of a company will be measured by its ability to leverage data through solutions such as: Advanced and Predictive analytics.
The benefits?
Improved customer relationship and satisfaction (41%)
Efficient IT operations and processes (39%)
Product and service innovation (35%)
In companies, departments leading Advanced and Predictive Analytics projects are primarily the sales, customer service, and marketing sectors. Specifically, according to the study conducted by IDC, CRM and customer analytics will improve customer satisfaction and retention by offering better and more personalized service. Furthermore, they will drive increased sales by enabling processes that increasingly rely on automation. This is where a more personalized relationship with customers is created and developed through the use of artificial intelligence in customer analytics.
We conclude by saying …
“Not always does change mean improvement, but to improve, you must change.” Sir Winston Churchill. It is indeed true: to grow, change is necessary. Being open to change is a true attitude, and today for many, it has become an urgent necessity.
And it’s not enough to invest in innovative technologies, because for businesses, especially those aiming to stay in the market over time, evolution is the healthy transformation. In fact, to evolve, companies need strategy, skills capable of harnessing the substance contained in data, as well as intelligence and the will to give it meaning, accelerating an inevitable process—one that aims for efficiency and security. Among the areas to focus on is certainly training, the only one capable of expanding and strengthening skills. We at Artmatica, since the company’s inception, have always focused on technology, the core of our daily operations, but most importantly, on a growth path that cannot and should not disregard the training aspect. So, let us be immersed in data and its ability to analyze in detail everything that is measurable, embracing change, and therefore competitiveness and growth.
