Data is the new oil, they say. Whether that is true or not is a discussion we can have another day. What is clear to me is that data is certainly the key to the success of your new startup, especially if it is one that provides products and services for mass consumption.
Some of the world’s most successful companies have bet on data. Take Amazon, for example: Guru Hariharan, a former Amazon engineer who now runs Boomerang Commerce, recently revealed that some managers at Amazon had boards outside their offices that read “In God we trust. The rest, bring me data”, a version of legendary American entrepreneur W. Edwards Deming’s famous quote. It explains why the Amazon application on your phone collects so much data. At the same time, it also explains why Amazon has excelled at almost everything it has tried.
My personal experience with data has not been very different. A few years ago, I was managing an ed-tech startup that is now a successful and established brand in Russia, the former Soviet republics and Brazil. All I can say in hindsight is that my bet on data paid off well. Let me talk about the lessons I learned as I experimented with data.
1. Start from the very top.
As the leader of the team, the culture of using data for decision making should start from your office, at the very top of the chain of command.
Data will give you direction. It can help you identify the part of the market that is underserved or the trends emerging in your sector. With data at your disposal, you will know where the energies of your team should be focused for maximum benefit. You won’t have to take a plunge blindly.
With data, you will be able to guide the company’s strategic vision, which is very important to give direction to the team in the early days.
You must lead by example. It will help in fostering an analytical mindset.
2. Choose the right metrics.
Given that the world has taken to the use of data the way honeybees take to rose, there’s tons of data available on every possible sector. For optimum results, your team should be able to identify the right metrics. The metrics will depend upon various factors, from the industry you are working into the size and cost of your product. But once decided, metrics for a particular purpose will always be the same. Thus, it may be difficult to do, but it is at best a one-time investment that will pay off every day.
Like coal, data is of many qualities. You will also have to inculcate the habit of separating bad, useless data from the meaningful numbers that are really helpful. Unless this is done, using data will bring diminishing returns.
With the right metrics, your managers will get good results, which in turn will inspire them to continue using data.
Remember what Angela Ahrendts, who was until recently the vice-president of retail at Apple Inc, said recently about data: “Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win.”
3. Make your data scientist part of the core group.
This is perhaps the most important step. In most cases, data scientists operate in one corner of your office, separate from your core team. As a result, there is little to no interaction between your core team of managers, who take the most important decisions about your business, and your data scientists, who share their findings in the form of trends.
When data scientists are part of your core team, they understand the nuances of business and are able to find solutions to real problems using data. At the same time, your managers will understand the nuances of data analytics, which will help them identify the issues they can resolve using data. Thus, there will be no unrealistic demands on both sides.
Together they may be able to do what they can’t do alone.
4. Improve data literacy
Data analytics is a constantly evolving field. As the volume of data increases, you will need better tools to analyze it. But, in a rush to update your tools, don’t forget to upgrade the skills of your team.
If your team is skilled at using data to find answers to their problems, they will go ahead and do it. Without the skills, they will struggle and give at some point. Investment in data analytics skills is important to foster a culture of data-driven decision making.
You don’t have to turn every employee into a data scientist but equip them with the basic skills to understand data. At the minimum, they must have the skills to know which problems can be solved using data, if not the skills to use the data on their own to solve the said problems.
“The ability to take data – to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it – is going to be a hugely important skill in the next decades,” Hal Ronald Varian, who is the Chief Economist at Google, said a few years ago. Or, as Carly Fiorina, ex CEO of Hewlett-Packard, recently said, “The goal is to turn data into information, and information into insight.”
Make sure your team keeps up with the data revolution that is underway.
5. Invest in data collection
This is the most obvious of all steps. While third-party data can help your business, it is better if you collect your own data.
You must invest in secure and accurate data collection. You will own the data, and the insights you derive from them will be known only to you. That is not the case when you use third party data.
With a constant stream of data trickling in, your team can be trained in the end to end use of data, from processing to presentation and reading. Data then becomes integral to your business operations. What better to foster a data-driven culture than making it part of your core operations?
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