Industries evolve, and businesses grow. It’s either that or both risk death. The evolution of modern-day business has catapulted data to the forefront of business consciousness. Consequently, the laggards of the business world have followed suit to reap the dividends of the data revolution.
However, there’s no benefit to using data without reliable datasets. Broadly speaking, there exist two types of datasets: external and company datasets. The former consists of primary or secondary data obtained to provide an understanding of the market, industry, competition, and factors outside the company.
Company datasets, on the other hand, come from within the company and are unique to its blend of employees, methods, and outcomes. Businesses can generate competitive edges from both data types, but that is impossible without understanding the data types.
With that in mind, this article explores the information obtainable from company datasets and how to achieve excellence with them.
What Types of Information is Available in Company Datasets
Company datasets include all data types obtainable from within an organization, ranging from basic employee demographic data to operational outcome metrics.
Specific examples of the obtainable data points are production metrics, revenue, expenses, etc. Below is an in-depth breakdown of some of the types of information in company datasets:
- Quantitative information. These are numeric conclusions that give an objective view of details. For instance, financial information like expenses, revenue, profit, loss, etc., combines to help accountants and relevant personnel understand the financial health of the organization. Similarly, numbers relating to the supply chain and operation would confer an understanding of product movement and operational efficiency, among others.
- Qualitative information. Not all information retains its insights when expressed in numbers alone. Qualitative information is one such category of company datasets. The source of qualitative information from within organizations is usually a survey. Companies use workplace surveys to assess employee performance, communication, punctuality, relationships, collaboration, etc.
- Operational information. Information within this class might be qualitative or quantitative, but it concerns the operation side of the business. As such, performance metrics, production benchmarks, targets, etc., fall into this category.
- Customer Information. Proprietary information generated from clients’ customer journeys is also obtainable from datasets. Businesses are in the special position of catering to the needs of their customers via sales or customer support. As such, they are able to collect data on pain points, payment methods, customer profiles, etc.
Besides the above, there are other types of valuable information in company datasets. Even some forms of primary external data may pop up. Data collected from primary sources are dependent on the scope of the exercise.
The objectives also influence the types of data collected and how businesses use them. As such, a dataset can be uniquely held by an organization despite not originating from within it.
Example of Companies Achieving Operational Excellence Using Datasets
There is no shortage of businesses that have leveraged data into operational excellence. However, like every other aspect of business, some people have done this better than others. That said, here are examples of companies achieving excellence with company datasets.
- Amazon. The multinational behemoth Amazon uses company datasets to achieve operational excellence. It does this by applying data to its supply chain optimization and using it to predict demand. The most popular, though, is the use of data to inform its product recommendation algorithms. The recommendation engine is arguably the most noteworthy aspect of the Amazon e-commerce marketplace, and it is data-driven.
- Tesla. The company is famous for its automobiles, but its activities with and for data also attract lots of attention. So much so that some have taken to calling Tesla a data company. Internally, the company uses data from its electric cars to identify areas of improvement in battery design and its auto-pilot technology.
- Google. When it comes to companies that deal in data, there is arguably none as big as Google. Through their services, they collect lots of data to inform improvements in features and updates.
The Future of Company Datasets
As technology advances, data use will evolve to accommodate new possibilities. With that in mind, current breakthroughs offer glimpses into what company datasets can do in the future. Here are some of the said glimpses:
- Further implementation of artificial intelligence and machine learning algorithms in predictive analytical models. Such measures may raise the accuracy of forecasts to unprecedented levels.
- Increased adoption of blockchain technology. Organizations and businesses could capitalize on the integrity and transparency provided by a blockchain. Technology would certainly improve collaboration without harming security.
- Introduction of comprehensive, more binding data privacy regulations. Given the rise of privacy concerns, this would impact the collection and use of company datasets in the near future. The tricky part, though, is predicting how comprehensive they would be and the consequences of poor adherence.
Conclusion
Many companies owe their business reputations to intelligent use of data. Company datasets are the type of data they have leveraged for their success.
Therefore, the evidence is out there, and the jury has decided that company datasets are effective in driving growth. It is time to figure out the types of data your business generates and how they can be of use. Do that, and the next level beckons.