Can Data Analytics help a Startup?
Level one or startup is a fledgling founded on a shoestring operation by one or more entrepreneurs bringing forth a unique concept/idea, with first funding from the founders or their friends and families. It is akin to a newborn in a family. Here roles are intermingled and not defined structurally. Level one organization provides increased autonomy, improved adaptability and higher flexibility to these professionals who are in an eternal hunger to seek more in their ever-growing quest for experiences.
Characteristics of Level one/startup
To launch a startup it takes immense belief in oneself coupled with defying the laid down statistics that one in every start up tends to be a failure. For startups to thrive, it should be supported by a good and robust eco system. Startups are characterized by the following features .
1. They are more in synchrony or harmony with what the market wants. It needs to be continuously innovated upon to find the right product-market mix, lest you become stagnant and very soon obsolete.
2. It is vital to start small and slowly expand while adjusting and accommodating to the changes.
3. They test the waters with their theories of disruption often displacing established businesses.
4. A close-knit work culture over traditional office settings.
5. Startups can change fast; They can incorporate new tools and culture just as easily as making an omelet. They do not require a highly defined implementation or change management process, which can save a lot of money during pivoting or transitions.
Challenges of Level one / startup
1. The first challenge for a startup is to prove the validity of the concept to potential lenders and investors.
2. Startups are always riskypropositions,but potential investors has several approaches to determining their value.
3. The complexities of regulatory bodies make it difficult for creating ambient conditions and add to their woes.
4. Non-availability of qualified employees, attrition rates and lack of deep pockets to hire the best is another significant factor as most of the skilled employees opt for cushioned work environment which revolves around stable jobs and clear-cut structures.
5. Tackling competitive landscapes and surviving in a price sensitive environment is another area where startups can be put to test.
6. It is wrong to say that millennial employees are changing the workforce culture. Rather they seek organizations that provide work life balance, social responsibility, personal and professional development.
How is data analytics useful for Level one / startup?
Every startup swears by their idea and believes it can make a radical change in the business circuit. To ensure that they are staying afloat it is important to record all their transactions, analyze them and take corrective decisions. Data is more than just numbers and figures; Data collection is often a tricky state for startups, who most likely assume that they know all what is happening. Often collecting their critical data like expenses, incomes, other accounting matters, leads, proposals, closures, and sales efforts is especially important but often looked down at. The startup environment is simple in terms of data and most of them can be captured in spreadsheets. There are several tools available in the market that provide these services at a very minimal cost. These can easily help shape future decisions if incorporated in the right manner.
Here are the few tips a startup should focus on:
1. Primarily, a startup should look at collecting more of its data and laying out systems that can collect and store their information more cost-efficiently.
2. Simple descriptive analytics rules the day for startups. They most likely know more details about their operations and finances. They need a place to store and download their information.
3. In case the startup thrives in an environment where the transactions a large, they should look at applications to manage operations. For example, a restaurant getting orders should definitely have a billing and operations management software to streamline operations. Or a stand-alone Lab, should definitely have a lab management software to make operations easy.
4. Startups tend to drive businesses through their team’s networks. It is here that startups should focus on the Diagnostic approach by understanding who your leads are, network and how they can help in your business development.
5. From a predictive point of view, startups should be up to date on market research within their area of expertise. A suggested research should be 95% External Market and 5% Internal capabilities. External market analysis is extremely critical to pivot or develop your product / service in line with the future market demands. Metrics like Compounded Annual Growth Rate (CAGR) for the industry is critical not just for identifying investors but also to survive and grow.
Thus, a data driven start up is definitely a Himalayan rocky ride to inevitable success.
Author: Jerrin Thomas ; Co-Author: Benila Jacob
