Data Loop Is The New Buzz Word!
“Data” is a highly valued asset in today’s connected world. Businesses across the spectrum are exploring ways and means to harness this data. The use of data is altering the way business operates across industries. Earlier, gathering a huge amount of data and analyzing it was restricted to huge corporations with big budgets. Today, small businesses too have to use the massive amount of data available. It helps them make smart data-driven decisions.
Although most of the data analysis discussions today concern large enterprises that can hire scientists and research firms, there are several tools that small business can use to gather, analyze and make sense of data they already have. It becomes all the way more important for small and medium organizations trying to scale up the operations with limited resources, to make well-informed decisions.
Introducing “Data Loops”
Data Loop is a continuous, iterative process of capturing and analyzing data, getting valuable insights, translating into action items and ‘looping’ the process all over again. Implementation of Data loops in the right format can help any sales-driven organization to unleash the maximum potential of their workforce and make better decisions, faster. In this article, we will try to address the basic concerns and queries pertaining to the data loops.
How to implement Data Loop?
Understanding the problem statement- This step involves investigating, analyzing and discussing your business model to identify the challenges in your organization. The challenges across different business functions should be addressed and quantified in terms of metrics.
Linking all the sources of data- In order to generate the most significant actionable insights, it is imperative to interlink and blends all the sources of data.
Collecting data- The data should be collected across all the business operations. With an automated data collection system, large volumes of data could be collected without any manual intervention.
Exclusive KPIs for your business- Every business is unique in terms of its scale, industry, value proposition, target audience, etc. Therefore, it is equally important to identify the KPIs specific to you and your business model. This is the step, which involves elaborate discussions with the data scientist or business intelligence analyst.
With advanced analytics, it has become all the way more easy for the businesses to collate data across different formats, functions, and sources and define KPIs, that are actually significant and consequential for a specific organization.
Identify actionable insights- Last but not least, identify the most relevant actionable insights to discover new growth opportunities and identify the roadblocks in your current business model. Sometimes, the insights generated may be overwhelming and might not be practically feasible to implement them in the short term. It is extremely important that the insights are prioritized in accordance with the short term and long term objectives of the organization. It’s even more important to ensure that the insights are relevant and effective, so set SMART goals for your insights- ‘Specific, Measurable, Attainable, Realistic and Timely’.
Now the bigger question- why implement data loops?
Data loops have a very significant impact on the alignment of sales and marketing strategy with activities, that increase the customer conversion and retention rate. The data loop enables the organizations in understanding the connection between the first interaction with a potential customer, to the time they actually become a customer. It also includes their overall experience with the organization, in terms of product service and grievance redressal. It explores the possibility of recurring transactions and upsells to the existing client.
Data loops can also be used to extract insights to achieve optimum resource utilization. Resources include deployment of manpower as well as machinery. For instance, Shell uses data crunching to save millions of dollars, which were lost before due to machine downtime. The oil industry giant employed advanced analytics to plan purchasing, placement, and disposal of the machine parts. It has reduced its inventory analysis from over 48 hours to less than 45 minutes, cutting off millions of dollars a year off the cost of moving inventory.
In conclusion, the organizations need not be aware of the jargons like Business Intelligence,Data Visualization, and Customer Retention’ to leverage Analytics for their business. However, it is challenging to analyze the quality of data and validate the insights, irrespective of the size of the organization and data volumes. We, at Jungleworks are striving to help simplify and help you understand data and make smart decisions. Feel free to write to us at [email protected] or you can Click Here to connect with a data scientist to address all your queries and feedback.