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4 Winning Strategies for Adopting Big Data Analytics

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StrategyDriven Organizational Performance Measures Article | 4 Winning Strategies for Adopting Big Data AnalyticsIf you’ve decided that now is the time for your business to make the transition to Big Data Analytics; great choice. Not only will you be able to analyze and process much more relevant information than before – you’ll also be able to begin putting it to good use as your business ambitions expand. Here are 4 winning strategies to help you with adopting BDA and take your company to the next level.

What is BDA?

In the simplest terms, it’s a service that allows the user to process huge amounts of data and then use this information for analysis purposes. The only drawback is that the greater the volume of data, the more likely errors and false readings are. With that being said, there are parameters that can be set to reduce the chance of this. With the above in mind, let’s begin with our strategies.

Turn your data into intelligence

The first strategy on our list is a pretty straightforward one, as it relies on what BDA does best – collecting data and compiling it for easy navigation. By embarking on a new campaign, any data that you use can be refined and then processed in an orderly fashion. With this data, you can then gain insights into a particular demographic, a target audience, the potential for conversions, and much more. The more you know, the better equipped you’ll be moving forward.

Cost reductions

Another great way to adopt big data analytics is in an effort to reduce your costs. The data being processed doesn’t only have to be external – it can be internal too, meaning that you could analyze the performance of your own business and see where specific costs can be cut. This can also be done via data analytics consulting, whereby you hire an expert to analyse the information presented and then create a report for you to use to reduce expenses.


Developing products with greater insight

If you’re in the process of creating a product, or if you’re about to introduce yours to the market, what more efficient way to identify key behaviors from potential customers than with BDA? By performing a detailed evaluation and then reading results from a chart, you can see where to dedicate your sales and marketing efforts, ensuring the potential for maximum reach.

Market insights

Complimenting point 3 above, BDA also allows detailed market insights including trends, customer behavior and patterns, and other important aspects to be considered. Adopting BDA in this way can actually force a business to pay attention to the finer details, albeit in a gentle, efficient way. The more insight you have into a market, the more likely you’ll be to achieve your aims.

Final thoughts

And there you have it – 4 great ways to adopt and utilize Big Data within your business in a way that promotes productivity, enhances the possibility of profit, and maximizes your chances of understanding your target demographic. Once adopted in full, you’ll quickly begin to see why so many people are turning to the potential of BDA.

Do You and Your Organization Speak Data?

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StrategyDriven Organizational Performance Measures ArticleSpeaking two languages makes you bilingual, and speaking three makes you trilingual. Any more than that, and you are a polyglot. In today’s data-driven business world, you are a data scientist if you can “speak data”.

Our world is becoming more and more about the data it generates. As pressure mounts, people who can analyze, visualize, and interpret data are becoming indispensable, much like a well-versed polyglot who can interpret and translate multiple languages with ease.

Speaking the language of data

Data surrounds us, and the ability to understand and interpret it should be a natural requirement for every individual and organization. Perhaps data and its projection on every surface of our surroundings will be the world’s new sign language. Thus, the new generation of human capital must possess this fundamental skill.

As individuals, we are challenged by the overwhelming amount of data we interact with in every scope of our lives. Learning how to make sense of data is becoming a necessity rather than a choice. If we want to continue to be part of this fascinating and engaging ecology – the world of Big Data, including the smart appliances, classrooms, schools, workplaces, and cities we anticipate in the near future – we need to be able to go beyond just speaking the language of data.

Using a data-driven strategy as a competitive advantage

It does not take a sophisticated algorithm to see the value of data scientists on today’s organizations. Clear distinctions are emerging between organizations that embody and embrace the data-driven world we live in and those who have not adapted and are still following a traditional approaches. Competitive organizations are embracing big data and re-engineering their strategies and processes accordingly.

In essence, these organizations are expanding their family of employees who are well-versed in data at every level of their managerial hierarchy. Clarity and transparency are of the utmost importance to data-driven environments where everyone speaks the language of data.

First and foremost, organizations have limited choices in today’s extremely dynamic business world. Data-driven strategies are inherently dynamic strategies that can help organizations bring the necessary transformations based on materialized and projected evidences. Data-driven strategies are also inherently granular, allowing management to sync and assess different layers of decisions and actions. Furthermore, data-driven strategies permit clear communication, responsibilities, and accountabilities at various decision layers.

Creating a data-driven culture

More importantly, the benefit of speaking the language of data allows organizations to be active in their communities and to learn through continuous engagement and feedback from their stakeholders. These are realities no organization can ignore for survival. However, in order to be competitive, organizations need to delve into the nitty-gritty of the language of data: the grammar, punctuation, and spelling that are required to be proficient in the world of big data. It not only requires passion, but also a bit of obsession.

Eloquent data speakers such as Google, Facebook, and Amazon serve as great role models for other organizations that are encouraged by the returns they see and that understand the growing need for their employees to communicate through data. This shift is not limited to creating a subset of employees who can analyze data, but to create a data-driven culture and environment that embraces all employees’ internal and external interactions as members of the big data ecology.

About the Author

Anteneh Ayanso is an Associate Professor of Information Systems at Brock University’s Goodman School of Business. He is certified in Production and Inventory Management (CPIM) by APICS and teaches and researches in the areas of data management, business analytics, electronic commerce, and electronic government. Anteneh Ayanso can be contacted at (905) 688-5550 x 3498 or [email protected]

Direct Use of Production System Data for Organizational Performance Measures

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StrategyDriven Organizational Performance Measures Warning Flag ArticleData access frequently challenges metric developers. Consequently, they may resort to using the most readily available performance data; data that can be obtained through a user defined production application query and downloaded into a Microsoft Excel spreadsheet or Access database.

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Strategic Analysis Best Practice 7 – Diverse Models

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Solutions addressing today’s multifaceted business challenges and opportunities can be extremely difficult to recognize; the ever increasing pace of change within the business environment further complicating this problem. In order to successfully deal with this challenge, decision-makers need the support of people and tools to help them distill large quantities of data, recognize important business trends, discount temporary fads, and translate their findings into meaningful organizational activities. Because no one analysis perspective will adequately account for all of the important nuances associated with a complex problem, multidiscipline teams and diverse tools should be employed to establish a complete picture organizational performance and environmental conditions. Use of a diverse set of models during the strategic analysis process helps create this needed picture.*

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