José Luis Florez Managing Partner of Accenture Analytics in Spain.

Transcription

1 Science and art in decision-making José Luis Florez Managing Partner of Accenture Analytics in Spain. 50 h a rva r d de u s t o bu s i n e s s re v i e w

2 Science and art in decision-making Faster markets, global competition and changes in the make-up of demand all combine to make decision-making in organizations an ever more demanding and complex task. Analytics can help management realize the full potential of any information their organizations can access. T he digital era has brought new and unprecedented opportunities for data exchange. The enormous amount of data generated internally and externally provides companies with an opportunity to understand in greater depth what is going on in their sector and the habits, desires and needs of their consumers. In a complicated and ever-changing environment, with few opportunities to rectify mistakes, the great challenge facing organizations is to turn that data into real knowledge. In recent years, the business world has changed drastically. Since the beginning of the economic crisis in late 2008, public- and private-sector organizations have been forced to rethink their strategies to compete in an increasingly uncertain and exacting environment. With limited resources, it is all the more necessary to use those that are available more efficiently. Because of the uncertainty, many companies are taking action with no clear idea of where they re headed and whether they re going in the right direction. There are fewer and fewer chances today to amend actions that don t bring the desired results: given the speed with which businesses have to move and the extreme competition they face, only the first to get things right will succeed. New technologies have made it possible to develop systems and procedures that can aid management and decision making. Data can now be turned into information, which firms then need to interpret to convert into knowledge. Without this final step which depends on each organization s internal capacity the process is pointless; there s no use just having information if you don t translate it into real knowledge. Business intelligence systems have come a long way since they first appeared. Many companies have adopted their own internal systems ERP and CRM are well-known and widely-used instruments, and are fully incorporated into business and corporate lingo. However, the challenges of the current environment call for something more. Companies need to take an extra step to ensure that the knowledge brings even greater added value to the organization, in order to ensure that new instruments contribute to making faster and more efficient, precise and appropriate decisions. It s not enough just to have a transactional view, based on what has already happened. You need to In a complicated and ever-changing environment, with few opportunities to rectify mistakes, the great challenge facing organizations is to turn data into real knowledge s e p t e m b e r

3 Table 1 Some of the most important advantages in the use of analytics Detecting possibilities for improvement and reducing ineffectiveness or unnecessary overlaps. More efficient use of the scarce resources available. Transformation of data into relevant knowledge and information. Improved decision-making. Gaining an important competitive advantage. More exact knowledge of the needs and tastes of the market and customers. Increase in innovation capacity to launch relevant offers and improve the customer s experience. Tangible benefits and high efficiency. Measurement of the economic effect of decisions. Speaking in euros. add an analytic vision, making it possible to foresee what is going to happen and thus optimize decision making. Historical data versus predictions Until recently, technological systems were geared towards providing information on past events; if an organization was working on promoting a certain product, for example, the technological environments might provide information on the number of new subscriptions. By examining historical data, this type of descriptive analysis could help companies answer questions like What happened? or How useful or detrimental was a particular measure in terms of results? Based on this information, the people in charge could act in consequence. In other words, their actions were reactive. However, if organisations are to be really competitive, just making do with studies of past efficiency and the success or failure of previous actions is not nearly enough. Reactivity must give way to proactivity: in the pressure of an uncertain environment, companies must be capable of knowing in advance the possible consequences of any decisions they may take. In this new scenario, they have to replace a hypothesisbased approach with more certain knowledge and more accurate forecasts, provided by the capacities of analytics. Using sophisticated mathematical algorithms based on statistical and econometric models and prediction, it is possible to perform complex and dynamic research, studying a wide range of variables. So, to use the previous example, organizations can analyze the possible success or failure of a development they plan to introduce before it has been developed in other words, anticipating the repercussions of their actions and avoiding unwelcome surprises and wasted investments. New analytics systems allow companies to advance faster, more flexibly and on firmer ground, extracting large quantities of information through a process of inference. What marks out successful organizations is their capacity for immediate action, based on real information, as opposed to conventional suppositions or ideas that limit growth. Advanced data analysis is changing decision-making in all sectors, in both strategic and tactical fields. Today, the tools to aid efficient decision-making are widely used and available to organizations; they are becoming more democratic and can now be applied to any area of management, be it strategic or operative. From the supply chain to sales, by way of marketing and pricing, the techniques of analytics shed light on decision making in a complex, uncertain and increasingly hazardous scenario. Nonetheless, one important caution needs to be made: analytics is not just technology. 52 h a rva r d de u s t o bu s i n e s s re v i e w

4 Science and art in decision-making Organizations have to lay the right foundations internally and must meet a series of conditions to provide the right breeding ground for developing their analytical skills. Analytical culture and talent One of the first prerequisites of proper analytics is the availability of processed and homogeneous data. However, the data and the technological analyzing systems are not in themselves of any value. What creates valuable information is the organisation s capacity for data analysis. And for this analytical capacity really to be turned into a competitive advantage, it is essential to develop an in-house culture that accepts and empowers it, in such a way that staff are capable of acting on the basis of that knowledge. Accenture says that one of the characteristics of high performance organizations is the presence of leaders who are capable of using analytics technologies that serve the business s strategy. Their vision gets filtered down throughout the organization to middle management. They in turn identify the best measures, make decisions based on the best available data and understand the importance of taking immediate action based on these decisions. One of the characteristics of high-performance organizations is the presence of leaders who are capable of using analytics technologies that serve the business s strategy Another priority for organizations must be to select, motivate and retain the right talent with analytical skills. There are still relatively few companies that manage this type of talent as a strategic resource. Indeed, they have often failed to identify people in the organization with this skill set and have no idea how many of them there are or where they are in the hierarchical structure. The result is that they have no specific training plans to promote these skills and they fail to capitalize on the potential strategic advantage. Whereas formerly, the largest amount of investment in training used to go on upskilling staff in IT, over In contrast to this ideal situation, one of the most frequent scenarios in organizations is that analytical skills and talent are kept locked up in isolated departments and fail to spread to other areas of the organization. The existence of these so-called silos is very detrimental to the development of real analytical capacity, which requires interdepartmental and inter-functional cooperation. To prevent this situation arising, organizations must encourage internal collaboration and joint work between different corporate areas and appoint someone to be responsible for developing analytical skills. One powerful way of eliminating silo mentality and encouraging connections between different areas of the company is to create repeatable processes for integrating analytics in day-to-day work. s e p t e m b e r

5 In the competitive environment of chess, good players need two key skills: capacity for analysis and speed in decision-making, all with the purpose of creating value the next two decades we will see an increase in plans designed to develop and integrate analytical skills in organizations. Checkmating reactivity! A fine example of the use of analytical talent can be seen in Viswanathan Anand, undisputed world chess champion since Anand, who successfully defended his title in 2012, is the only player to have won the championship in all the major formats. In the competitive environment of chess, good players need two key skills: capacity for analysis and speed in decision-making. The goal is to create value which in this case, means beating the opponent. Despite changes in the game resulting from the emergence of computers, striking a balance between depth of calculation and expert intuition is still essential to devising a winning strategy. In the business world, the approach is similar: it is essential to have the internal capacities for correct analysis and decision-making, all at the highest possible speed. In this case, the goal is to obtain tangible business results; organizations that manage to gain ground on their competitors will have a competitive edge. It is therefore vital for organizations to have these skills and the necessary analytical talent in house and they have to attract the best analytical minds. The capacity of the leaders, collaboration between different areas and the right talent management all go to form part of building a solid culture of support for analytics technologies and skills. Organizations that use this philosophy will be able to maximize the return on their investment and make decisions faster and more effectively, involving the entire organization. Analytics is not just a technological solution; it is a new way of doing business, based on statistical certainty and prediction. Science and art in decision making. Ediciones Deusto. Reference No h a rva r d de u s t o bu s i n e s s re v i e w