For many years now, business leaders have emphasized the need for data-driven operations. Organizations, big, small and everything in between, have realized the importance of capturing abundant data to truly fathom the state of their business and to strategize for the future. This data may range from performance metric of individual employees to Big Data obtained from a wide array of sources. However, that used to be the case.
Rapid advancement in digital technologies has now necessitated that businesses strive for differentiation in order to beat steep competition. Differentiation can only be attained with actionable insights, not simple data. As per The Economist Intelligence Unit and global sales and marketing firm ZS, on a broader scale, investments in analytics solutions are yet to pay off and admittedly, organizations across the world are still struggling to draw said insights from their data. Some of the challenges towards achieving actionable insights include inconsistent quality across data sources, inability to process data as quickly as it materializes and disrupted visibility into customers’ data across all channels.
What is the difference between data, information and insights?
Erroneously, many think that data means information, which, in turn, means insights. While that may be a passable connection when the general sense of the terms is considered, in business that connection seems vague and therefore ineffective. In fact, the difference between the three can be better understood with a hierarchy pyramid.
- Data generally refers to the unprocessed facts that are obtained in the form of numbers and text. Measurable data is quantitative while observable data is qualitative. Data is available in computer-friendly formats and stored in spreadsheets and databases.
- On the other hand, information is data that has been processed, aggregated and presented in a more human-friendly manner which provides more context. Information may be presented via data visualizations, reports and dashboards.
- Insights are generated through thorough analysis of information and drawing of conclusions. It is noteworthy that data sets the stage for information, information then leads to insights that hold the power to drive necessary change.
- Actionable insights sit at the very top of the data pyramid. An insight that is specifically generated to suggest the next course of action is definitely more effective, and therefore more valuable, than an insight that only provides information, often an answer to a question.
What makes an insight truly actionable?
The key attributes that make insights truly actionable are the alignment, context, relevance, specificity, novelty and clarity. Thus, the insight that is extracted should be well-aligned with the business’ goals and strategies, have a comparison or benchmark to provide proper context, be delivered to the right person at the right time, be specific so that it can be acted upon, offer more information than other more familiar insights and be unambiguous enough to be easily understandable. For example: the Business Intelligence solution delivered by Embee to a leading jewelry house, helped them to break down their sales data by individual stores, trends, demand, etc. It revealed depleting demand for a particular design at one store, while another store was experiencing an increased demand for the same. Minimal adjustment in the inventory based on this insight resulted in improved sales instantaneously.
How can a business become truly insight-driven?
For most businesses, acquiring data is not the challenge, it is putting it to work. Being insight-driven means putting all that captured information into a single source in order to generate a comprehensive picture of how each internal and external factor is impacting the business and what should be the next course of action, considering all scenarios.
So, how can an organization achieve the said level of efficiency? It is by embracing four fundamental capabilities:
- Data should be easily accessible: By adopting data management technology, for example – advanced business analytics, that doesn’t strictly follow conventional, rigid analytical processes, one can successfully consolidate data from every source onto an easily accessible platform that can be accessed and acted on quickly.
- Analytical tools should be agile, flexible and self-serving: Fortunately, with latest innovations in predictive, prescriptive and self-serving analytical tools, one doesn’t need to have extensive knowledge about technology to make sense of data. The tools used should be intuitive enough to dig deep into finer details and suggest the next steps.
- Insights should be well-rounded and cover all areas of the business: Data volume has exploded in recent years but not everything is analyzed extensively yet for decision-making. All aspects of business must be tapped into to make the insights more comprehensive, practical and effective. This may be done by integrating applications into an ERP core that can manage large data volumes as well as process and present it in real-time.
- Insights should be contextual: Ignoring the learnings of past almost always result in complications in the future. That’s why data of the past should not be put to the side when implementing business analytics to draw insights. Contextual learning can render insights more accurate.
Everything that a business needs to succeed is already present in its data. Actionable insights extracted from it provides the guidance that the business needs to grow steadily. In today’s unpredictive marketplace, businesses cannot hope to succeed without robust analytical capabilities. Have you thought about incorporating a robust Business Intelligence solution in your organization yet?
