Big Data overdose
It has been 10 years since software startups started selling their Big Data solutions to tap into the high level of data the Corporate groups have and are not leveraging. I was one of them. The value proposition of this new technology is impressive and could have made a dent into the traditional business. It would have been possible if we were to dismiss (1) the internal process of management, (2) the political issue that is the access to DATA, and (3) the high pressure change in focus for any company (from product to customer centricity). Yet, large corporate groups as well as SBMs are still trying to leverage. And are failing because they didn’t identify the pre-requisite of the Big Data.
I have seen the Big Data market move a lot. Marketing data was and obvious focus but the data sources were too much spread within the company to be useable (internal issues of ownership and sharing) alongside the Business Intelligence units (too finance related to be tackled by frail startups, even though well funded). Then Big Data refocused on Advertising Data with the value proposition of improving the customer acquisition cost for companies, with in fine prints that it is only the visitor acquisition cost that would be improved. Definitely not the customer acquisition cost. Nowadays the calculation beast is looking into new ventures with (1) trying to directly connect with Finance, (2) HR, and (3) the Supply chain. But, like any software, it requires standard process. And that standardization requirement has generated an overdose for the customers of Big Data.
The important thing to keep in mind is not that Big Data would save the day. It is that to use a calculator, you need to identify a few things first. That may even help you deal with only simple math instead of bringing complexity at the table, which is always a bad, bad, idea. The few things to identify first before jumping into any “we have to do it because it is hype”:
- What is the objective of the calculation? For example: if you need a customer acquisition cost (CAC), you have everything you need and don’t need any Big Data engine to identify it (your total cost divided by the number of customers). Your vendors may need one, though, since you would need to ask them how to improve the CAC with a precise and understandable process (that is why you hare paying your vendors, right?)
- What is the business performance you want to reach? For example: if you need to find a needle in the haystack to improve your business, I would assume that you are not focused on what is critical since you are basically telling your boss that you need €10M within 3 years to find how to optimize your activities of 0,0X%. Spend the cash into innovation projects, the NPV is higher.
- Is your organization ready for data transparency? For example: opening the data box means that the company will see how and where they fail and all the stakeholders would be publicly facing their own responsibilities. You may want to deal with such a situation with a lot of preparation, because (1) everyone would be willing to hide things or (2) everyone would be willing to highlight items that are only relevant for internal political issues, thus preventing from any useful outcome from the Big Data.
The Big Data topic is something that has been around in the new technology companies since they need it to run their business (large volume a data coming from computing process). The way those companies handle their calculation challenge is a key differentiator for themselves. But it is totally irrelevant for traditional businesses that can’t identify a direct and tangible benefit from using a big calculator. The priority setting is not at that level, unless you are Amazon and you need to move such a large inventory on a daily basis. You need to focus on looking for the best trade between increase in performance and total cost of the project. And definitely, Big Data is at the bottom of the priority list.