• Ahmed Abaza

Why is Data the New Oil? (With Potential Applications)

A read on the importance of Data for companies and how it can be leveraged to grow businesses to new levels.

New Raw Material


Unless you were living in cave for the last few years, I presume the phrase “Data is the new oil”, coined by Clive Humby, is very familiar to you. It's mentioned, in every talk, meeting, doctor's appointment or gathering. The question is , Why this analogy feels so relevant today?


Well, I believe this analogy came from the premise, that Oil was a major contributor to the latest industrial revolution. It’s powering cars, electricity, and economies. Just like coal, steel and electricity, before it, oil is one of those resources that transformed our world. All of these raw materials basically led industrial revolutions, as the main element of human progress. Building on this, what do you think is the raw material for the digital age?


Yup! Data is..


So, it’s no wonder that even similar terminologies of Oil, such mining and refining are also used to describe parts of the data processing workflow. Although, Data is different.

Data, unlike oil is infinite, it can grow and scale quickly, there is no need to wait for fossils to decompose for millions of years, to be transformed to oil, nor do we need massive exploration expedition to get it. It's readily available to every one and every business, and we are generating a great amount of data everyday, with all the technology that surrounds us.


Better yet, all the tools to mine it, refine it, and make it valuable are available as ever!


Though, just like oil before cars and fuel engines, without refinement, data can be useless and even a burden. Its impact on progress and value can be very small or even wasting.


On the other hand, those who can mine, refine, distribute and process it into revenue making , and cost savings opportunity are at, an almost unfair competitive advantage, against their counterparts. Just like a horse racing a Ferrari, on a highway.


Data Asset Vs Liability


Mckinsey issued a report, mentioning that capturing only 40% of data value, can produce up to 60% increase in net margin for retailers and can lead to 25% of lower operating cost, in manufacturing, if only one was able to capture 30% of its value.


So, that said here are a few questions,


Is your data generating you Money?


Is your data a liability, that is taking money from you to store, archive it, paying people to maintain it, or is it an Asset, saving you costs, generating revenue opportunity and making your customers more happy, and more loyal?


So, how can one turn data from Liability to Asset?


Having a data workflow, by which you can mine, refine, process, analyze and distribute data, Money making opportunities can be limitless.


Apply business analytics, and build:

  • Descriptive Reporting:(What happened?) By which building complete visibility on all core operations

  • Predictive Reporting:(What could Happen?) By which you predict different outcomes, such as demand, price or returning customers

  • Prescriptive reporting:(What could be done?) By which you can simulate and build best Next Action case for every business decision.

They say that a picture is equal to a 1,000 words. Nothing is more true when it comes to data. Visualizing data, and making it human readable, facilitates decision making, and makes a business much more agile.


Not to mention, you can apply Machine Learning and A.I, to capitalize on the amazing power of superior analytics and automation, to optimize the business top-down!


Some Data Inspiration


Marketing & Sales:


  • Create more personalized, highly effective promotions,

  • Predict Customers who are about to churn, and save them from going to competitors

  • Increase conversion rates and reduce friction to conversion

  • Superior marketing campaign analysis, by analyzing cost-effectiveness, forecasting ad spend, and better customer targeting and segmentation.

  • Price your products at their optimal price points, to increase revenue, sales and profitability

  • Recommend products for customers who are most likely to buy and increase up-selling and cross-selling success rates.

  • Better manage sales force, and predict sales volumes and forecasts more accurately

  • Sales and profitability per product category, or vertical 

  • Build new, in-demand products, and beat competitors in being the first to market


Manufacturing:


  • Predict maintenance and downtimes, and always be ready with spare parts and planned maintenance schedules

  • Optimize inventory levels, SKUs, and keep a healthy fulfillment rate

  • Better manage your sales force, based on their performance

  • Create full visibility on cycle-times, on-time manufacturing, Production performance order fulfillment rates, and on-time shipping.

  • Optimize lead and lag times

  • Analyze and Diagnose overall equipment efficiency

  • Predict, diagnose and reduce production waste

  • Optimize operating expense ratios


Human Resources:


  • Predict employee turnover, and thus always have succession planning and proactive recruitment

  • Predict, and Analyze employee engagement levels

  • Analyze organizational structure effectiveness and communication hierarchy efficiency

  • Analyze employee learning and growth

  • Predict and analyze Employee Absenteeism

  • Strategy awareness and alignment

  • Revenue per Employee

Financials:


  • Predict credit default by different customers, and better asses risk

  • Optimize cash payables and receivables, and cash conversion cycles

  • Superior procurement planning and visibility

  • Accurate financial forecasts, and proactively avoid cash-gap risks

  • Predict Consumer Price Index and other market price fluctuations

  • Revenue growth rates and trends

  • Returns on innovations

Logistics & Operations:


  • Better utilize fleets, and logistics and get more out of your assets and distribution networks while optimizing delivery schedules

  • Predict product, demand for different branches, territories, to better plan and reduce supply waste and have more effective buying decisions

  • Predict and analyze project cost variance, schedule variance and risk

  • Analyze and visualize Asset capacity utilization

  • Predict Time to Market

  • Optimize Inventory shrinkage rates


Having the Data Discipline


Every business collects Data . It doesn't have to be digital, it can take so many forms. One should always be conscious, that the more data your collect, the more you can mine it for value. Data can be very powerful asset, for those who only can see it through this lens.

Founder & CEO of Synapse Analytics on how AI can be used in Retail. Synapse is a data science and AI company based in Egypt. Synapse Analytics

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