HOW DATA CAN improve decision-making?

Without a shadow of a doubt, data must be at the crux of strategic decision making process. Hence, nowadays it is not uncommon to spot a C-level position responsible of that crucial function; Chief Data Officer. In line with that, data can supply perceptions that support business to respond to its fundamental questions, such as; how can the business enhance customer’s retention and satisfaction levels? As earlier said, data guides to awareness, from which managers and business owners can take actions and decisions that boost the operations. Accordingly, at the outset of decision-making process, we should begin with the business strategy, as getting confused by the potentials which big data can provide along with getting lost in the hype surrounding data is quite easy. Hence, starting with a robust strategy can help to overlook the hype and focus on the difference that is about to have on business (Marr, 2016).

The subsequent step is to recognize the type of data the business wants to acquire or access. It is important to realize that no sort of data is integrally better than the other. Thus, business must emphasize on recognizing the best data for them, the one that possibly will assist them answering their most persistent challenges and bring on their strategic goals. As soon as the business identifies the data it needs, it is advisable to check if the business already possesses few of the sought information, even if it is not instantly noticeable. In-house data represents everything the business presently has or can reach. If the data is not available, then other methods of gathering can be considered, whether that is going to be executed through existing systems or by acquiring or accessing external data.

Subsequent to that, the process of data aggregation begins. Most of this stage depends on allocating the procedures and people who will collect and control the data. Business might buy access to pre-analyzed data sets, in which case data collection is not needed. However, what actually happens, many data endeavors demand some volume of data collection. Subsequently, the analysis stage commences, during which the business analyzes the data to infer useful and meaningful business insights, which will ultimately (if properly analyzed) offer a significant value to the decision-making process.

References: Marr, B. (2016) Data-Driven Decision Making: 10 Simple Steps for Any Business. [Online]. Available at: https://www.forbes.com/sites/bernardmarr/2016/06/14/data-driven-decision-making-10-simple-steps-for-any-business/#30ceb5675e1e. (Accessed: December 12 2019).

Despite the promise of AI, many organizations’ efforts with it are falling short

HBR in their July/2019 publication, had referred to one of their recent surveys where thousands of executives took part in sharing their thoughts of how their companies use and organize AI and advanced analytics, with the results being far from encouraging as 8% of surveyed firms engage AI in core practices that support widespread adoption. While the rest of them are only applying AI in just a single business process.

Why the slow prog­ress? At the highest level, it can be a reflection of a failure to rewire the organization, particularly that AI along with other promising digital transformation initiatives are facing formidable cultural and organizational barriers. Yet, if the business is blessed with a leader who at the outset take steps to break down those barriers, then they have a significant advantage of capturing the most of AI opportunities.