Mistakes to Avoid when Implementing Big Data

Companies in the FMCG sector or rather in general are aware of how Big Data is indispensable to their businesses and rush to implement the use of it. But if we are being honest, a consistent and beneficial data science journey that can bestow your entity as a “Data-driven company” is one of the hardest things to achieve.

The level of competitiveness in the FMCG industry goes to show that market research is no longer enough to win you market share. However, this coupled with strategic implementation of data can reward you with more than just market share. I am talking, improved customer experience, clear marketing goal and competitive advantage just to name a few.

I would advise business leaders to bank on data as a promising investment due to its high potential business value. Even so, your approach needs to be systematic an with an effective data strategy in place. Before you do, watch out for these common mistakes and quickly correct, if not avoid them.

  1. Biting More than You can Chew

Do not get too excited with generation of data that you end up with huge amounts of it and end up getting overwhelmed. Analysis of huge amounts of data can be cumbersome and if you ask me, can be confusing too. It will reach a point that projects supported by the data may stall due to ambiguity.

Start small and do not overanalyze would be my suggestion. Have a defined project that you do not stray from. This will help you make sense of which data to focus on. If you keep getting vague results, that is a cue for you to narrow down further until the results you get start answering your specific speculations.

2. Cost Inaccuracy

Taking into account only technical costs and disregarding every other supporting cost is a common mistake.

Depending on your implementation plan, create a proper budget with a before and after project. Factor in things like training, skills development, hiring of personnel with proper analysis skillset and any other expense necessity.

3. Speaking of Trained Personnel, A Business Intelligence Team

What good is data if it is not in the right hands?

Only the right person/ team would make good use of it and be able to gain the most valuable insights. Such a team is a crucial investment and with good use, will make a very high return on investment. Ensure you onboard an efficient and devoted business intelligence team that will always have you one step ahead, driving progress.

4. Disregarding Data Governance

Data security and governance should be every business concern. Its absence questions the integrity and questions the results obtained.

Have a robust system of process and controls that explains an understanding of the data possessed, auditing the manipulations of data, and holding control over the privileged users. Access should be granted with great scrutiny.

5. Answering the Why

Is there a defined and viable cause? If so, which?

An analysis of your business pain areas and what you seek to achieve should be clear. Otherwise you will be stuck with data that you cannot act upon as you are not aware of how to. As you are doing so, also set key metrics that will assist in contextualizing the data. Let them act as the foundation to results interpretation and key actions to be taken.

6. Under-utilization

Yes, you heard me right.

Hoarding and not utilizing data is indeed a common mistake and detrimental to say so at the very least.

Create a habit of inspecting your “Data Silo.” You’d be surprised of how judiciously you can use this stored data. From time to time make a point of extracting and thoroughly going through this data. You might just find insight you never knew your business was missing.

7. Ineffective Approach

I cannot stress this enough, PROPER EVALUATION AND PLANNING.

Anyone in business understands risks and benefits play at a level field. Thus the need for a proper investment evaluation before taking that step.

Some businesses take a leap and lay it all on the table only thinking about the benefits that will come in investing in data. In the event this falls short, recovering may take a while not forgetting the bitter aftermath it will leave you with. On the other hand, we have some businesses that approach this from a conservative view, holding back before finally making the huge investment missing out on the full potential of this investment.

Have an In-depth analysis of the already existing business standpoint laying out how data can aid in bettering the situation. This will help in setting reasonable expectations when it comes to the power of data.

In the end, Big Data is only effective when used the right way. You do this by assessing the need and implementing your data initiative with a plan to mitigate the risks. What will differentiate from the rest is how you come up with ways to deal with the above common pitfalls.

Catch you next week!

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