In today’s world, access to data is no longer a problem. There are such huge volumes of data generated in real-time that several businesses don’t know what to do with all of it. Unless big data is converted to actionable insights, there is nothing much an enterprise can do. And outdated data models no longer help in processing big data to derive insights.
When a business fails to gain actionable analytics and implement the data-driven model to improve decision-making, it ends up losing to competitors in the market. Despite having access to real-time data, the business will continue to be stagnant and passive because it doesn’t have the necessary setup to convert big data into actionable intelligence.
Many big data consulting companies offer offshore services to help SMEs and large-scale enterprises implement the data-driven model in their business by investing in advanced data analytics. Let’s read about big data, how it works, actionable intelligence and its benefits, and how to convert big data to actionable insights.
What is Big Data?
Big data is a trending technology which helps to handle a large amount of data that is complex to categorize and process using traditional data management systems. The Five V’s define the nature of big data:
Volume- Big data is huge and is constantly increasing in volume. It needs to be stored in data lakes or on the cloud.
Velocity- Big data is collected in real-time and is generated at a rapid pace. IoT, data streams, smart meters, etc., are always collecting data.
Variety- Big data is raw data and comes in structured, semi-structured, and unstructured formats. It can be images, text, audio, video, graphs, and much more.
Veracity- Since big data comes from multiple sources, it needs to be cleaned and processed before it can make sense to the end-user.
Variability- Markets are volatile, and data flows cannot be predicted. It is important to know how data is impacted by the changes and how that can, in turn, impact business decisions.
How Big Data Works
Big data analytics help you in deriving accurate insights. But for that to be possible, we need to know big data works.
- Integration of multiple data sources to bring real-time data to the enterprise
- Storing this data in on the cloud or on-premises so that it can be cleaned and formatted
- Using advanced analytics to work on big data and derive actionable insights
- Use data visualization tools to present the insights in an easy-to-understand format and speed up the decision-making process
The Need for Big Data and Big Data Analytics
Analyzing big data helps you to understand the market conditions, consumer behavior, the financial position of the enterprise, and several other vital factors that play a role in shaping the future of your brand. Due to the vast amount of data available, you cannot rely on manual data analytical procedures to gain insights. The following are some reasons why every organization needs to invest in big data:
- Make better decisions in quick time
- Become a customer-centric business
- Reduce the cost of investment
- Increase operational efficiency
- Optimize the use of resources
- Develop new products and services
- Take advantage of market opportunities
- Fraud and risk management
- Improve business flexibility and scalability
- Data security and compliance
What is Actionable Intelligence?
Actionable intelligence is an insight or prediction that can help you gain a competitive edge over competitors. It helps in making future decisions to improve the overall performance of the enterprise and keeping it ready to face the competition.
Actionable intelligence is one step ahead of business intelligence. It doesn’t stop at providing data insights. It provides you with a comprehensive plan to get the best possible results from the insights.
Benefits of Using Actionable Intelligence
Actionable intelligence is derived using big data analysis. It is mostly used for competitor analysis to understand how you can do better than them. At the same time, you also have to know where to draw a line. Aggressive data gathering attempts to know more and more about your competitor can be termed illegal and come under corporate espionage (corporate spying).
So, apart from the competitor analysis, what are the other benefits of using actionable intelligence?
- Get timely and accurate reports about cybersecurity
- Real-time threat analysis
- Contextual analysis to make rapid decisions
- Improving data security to match the threats
- Understanding the demographics of the target audiences
- Planning the marketing budget to increase ROI
- Aligning KPIs and analytics with business processes
- Empowering employees with accurate and reliable data
However, for you to successfully get actionable intelligence from big data, you will need to hire a trustworthy consulting company to help you establish the setup in your business. The success of your decision to use big data analytics will work when experts handle the job.
Steps to Convert your Big Data into Actionable Intelligence
Converting big data into actionable intelligence needs proper planning and approach. You need to work with the consulting company to first understand what you need for your business. Only then can you find the best way to make it possible.
Step 1: Know What You Want in the Long Term
Don’t let the traditional systems hold you back and limit the insights you can gain. Start fresh without excess baggage from the past and be ready to adopt new tools. However, it is also necessary to have a clear long-term plan for your business. Unless you know what you ultimately want for your enterprise, you cannot choose the necessary tools and software to reach the goal.
Artificial intelligence-based tools are used to process big data. But that doesn’t mean any such software will do. In addition, it does not mean that you have to invest in a company-wide adoption for the system to undergo a complete change.
All these come later when you know what your business should achieve in the next five years or so. Set a tangible target and start creating a pathway to reach this target. Focus on the most important goals instead of having too many targets.
Step 2: Identify the Factors that will Result in the Required Outcome
Since you know what you want to achieve, it’s time to identify the factors that will help you get the expected results. It is one of the trickiest parts of the process. Going wrong here would mean that your entire plan of action would be wrong.
For instance, if you wish to increase your customer base by 10%, you need to know what factors can help you achieve this. Should you target a new market or work on existing ones? Should you reach out to a different target audience? If yes, what changes do you need to make to the marketing strategy to attract new audiences?
Can all these be aligned and mapped together to become a part of a single process? Which step should come after which one? How can the factors be executed, and how many resources do you need to spend on it?
If you want to streamline your supply chain and decrease the delivery time in the next few months, you’ll need to follow a similar approach and find factors that influence logistics.
Step 3: Establish Goals to Achieve the Factors
Once you know the factors and how to handle them, it’s time to set goals for the teams. You need a deadline by which the goals have to be achieved.
Let’s continue with the same example. What are the steps involved in defining the target audience? How long does it take to identify a potential new market? By when should the marketing team start reaching out to the target audience? When should the sales team contact prospective leads and convert them to customers?
By setting a fixed time for each process, you’ll have a clear view of how long it’ll take to achieve the ultimate result.
Step 4: Identify and Integrate Data Sources to Measure the Factors
Now, for all of this to be possible, there’s one thing that’s a must. What is it? Data.
How else can you choose the target audience? How else can you create a marketing plan that will attract them? You need data, and you need it in real-time. Historical data has its limitations and can be used only to a certain extent.
You need to hire data management services to identify data sources, integrate them, and collect the data in a single place for further processing. You will need automated systems to collect, clean, format, and categorize data to help analytics work on delivering actionable intelligence.
Step 5: Convert Data into Measurable Metrics
By getting rid of duplicate and redundant data and structuring it in a standardized format, you can convert raw data into measurable metrics. Meta tags and categories help organize data in individual data sets.
Using performance scorecards is a way to establish metrics to assess how the factors are influencing the target. It is vital to present the entire information in an easy-to-understand format. Not every employee in the enterprise can understand the technical aspects. Also, you can’t expect employees to go through pages and pages of analysis to make a decision.
Step 6: Use Data Visualization Tools to Present Insights
That’s where data visualization tools help organizations present the analytics in a simple and effective format. Several AI-based data visualization tools are available in the market. Pick the best for your business and provide employees access to the interactive dashboard. It also helps in automating the processes to assist the teams to achieve the results in less time.
The easier it is to identify actionable intelligence and comprehend the reports, the sooner the teams can make a decision to achieve the target.
Step 7: Make Decisions and Implement Them
Once you know what needs to be done to have an edge over your competitors, you should put the plans into action. For example, if offering a discount on a product during a certain period will boost sales, you need to prepare the groundwork to reduce the prices and market the offer in advance. Your target audience should know you have something interesting to offer.
By aligning everything, you are using big data to derive actionable intelligence to achieve the goal of increasing your customer base.
Conclusion
Using big data technology is essential for enterprises to survive in the competitive market and expand the business. It is an integral part of digital transformation to adopt the data-driven model to make faster and better decisions based on reliable insights. Organizations can hire companies that offer cloud data analytics to streamline their business processes and move from traditional systems to modern systems.
