Digital transformation for SMEs, Part 3: Data analytics in the enterprise

data

This is the third article of a four-part series on helping SMEs chart the course of digital transformation. We will now look at digital transformation opportunities across the enterprise and understand the role of data analytics in helping SMEs make better decisions.

Where does Data Analytics fit in the enterprise (irrespective of the size of the business)?

Everywhere, is the short answer.

Data analytics fits in every department of an enterprise as different kinds of data are collected in each of them. Below is a quick view of departments and some use cases:

Departments Areas or Use Cases Brief
Finance

General Ledger (GL) Reconciliation Monthly General Ledger reconciliation could be automated to eliminate human errors and free up man-hours for better tasks
Fraud detection Vendor, employees, balance sheet, etc
Data aggregation Reading and aggregating data from various sources like pdf, Excel, databases.
Risk analysis Analysis of risks like business capital, investments, loans, customer segmentation, etc.
Velocity and Quality of decision Improved velocity and Quality of data-generated and decision took basis factual analysis by automating and eliminating human errors
Stock market insight Analysis of stock prices by more holistically modelling taking into consideration more variables
Procurement

Invoice and Purchase Order (PO) automation Eliminate errors and free man-hours. Pre-built reports and data queries run from inside the ERP System
Fraud detection Detect the fraud as it happens and take corrective measures rather than finding out at a later time
Vendor management Differentiating tail spends, saving costs
Bid and Spend management Spend and bid, cost benchmarking, Invoice compliance, Payment term analytics and Supplier risk and performance
Inventory Management Optimize costs, space and run production smoothly
Product Planning Profitability management A simple delta drill chart could explain, by removing which parts from the production line could the profitability have been boosted further
Shop Floor

Lower cost of production Reducing or eliminating costly unscheduled downtimes using Predictive Analytics
Quality improvements and scrap reduction Fault pattern identification and elimination
Productivity enhancements Resource Availability and Productivity enhancements
Near real-time feedback Take corrective measures without delay, as you get notified of actual scenarios near real-time
Human Resources Employee experience Measuring employee engagement, time to hire, retention rate, better planning and overall workforce management decision
Payroll reconciliation Automating the Payroll reconciliation process to avoid human errors and free up man-hours
Marketing

Customer behaviour Survey insights, trends
Promotion Promotion insights and optimization
Customer experience Combination of data and ML. Targeted messaging.
Dealer Management Drop laggards, cut costs on retaining dealers
Warranty Lower Warranty costs Lower or eliminate warranty costs by doing root cause analysis, identifying design and manufacturing flaws, eliminating fraudulent claims and claim processes
CEO’s office Management Dashboards The overall health of the company at fingertips: production quantity, quality, inventory, risk, profitability, costs, etc.

These common pain points businesses face can be transformed into growth opportunities through data analytics as part of the larger digital transformation journey.

Also Read: Digital transformation for SMEs, Part 2: Understanding its maturity cycle

While it may be overwhelming to cover all areas, starting with one or two key areas by prioritizing will contribute towards more efficient use of resources, risk management and better return on investment.

Stay tuned for our fourth and final article in this series. With the charting and planning in place, we tackle the implementation of digital transformation into the organization’s structure and processes.

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: wrightstudio

The post Digital transformation for SMEs, Part 3: Data analytics in the enterprise appeared first on e27.

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data

This is the third article of a four-part series on helping SMEs chart the course of digital transformation. We will now look at digital transformation opportunities across the enterprise and understand the role of data analytics in helping SMEs make better decisions.

Where does Data Analytics fit in the enterprise (irrespective of the size of the business)?

Everywhere, is the short answer.

Data analytics fits in every department of an enterprise as different kinds of data are collected in each of them. Below is a quick view of departments and some use cases:

Departments Areas or Use Cases Brief
Finance

General Ledger (GL) Reconciliation Monthly General Ledger reconciliation could be automated to eliminate human errors and free up man-hours for better tasks
Fraud detection Vendor, employees, balance sheet, etc
Data aggregation Reading and aggregating data from various sources like pdf, Excel, databases.
Risk analysis Analysis of risks like business capital, investments, loans, customer segmentation, etc.
Velocity and Quality of decision Improved velocity and Quality of data-generated and decision took basis factual analysis by automating and eliminating human errors
Stock market insight Analysis of stock prices by more holistically modelling taking into consideration more variables
Procurement

Invoice and Purchase Order (PO) automation Eliminate errors and free man-hours. Pre-built reports and data queries run from inside the ERP System
Fraud detection Detect the fraud as it happens and take corrective measures rather than finding out at a later time
Vendor management Differentiating tail spends, saving costs
Bid and Spend management Spend and bid, cost benchmarking, Invoice compliance, Payment term analytics and Supplier risk and performance
Inventory Management Optimize costs, space and run production smoothly
Product Planning Profitability management A simple delta drill chart could explain, by removing which parts from the production line could the profitability have been boosted further
Shop Floor

Lower cost of production Reducing or eliminating costly unscheduled downtimes using Predictive Analytics
Quality improvements and scrap reduction Fault pattern identification and elimination
Productivity enhancements Resource Availability and Productivity enhancements
Near real-time feedback Take corrective measures without delay, as you get notified of actual scenarios near real-time
Human Resources Employee experience Measuring employee engagement, time to hire, retention rate, better planning and overall workforce management decision
Payroll reconciliation Automating the Payroll reconciliation process to avoid human errors and free up man-hours
Marketing

Customer behaviour Survey insights, trends
Promotion Promotion insights and optimization
Customer experience Combination of data and ML. Targeted messaging.
Dealer Management Drop laggards, cut costs on retaining dealers
Warranty Lower Warranty costs Lower or eliminate warranty costs by doing root cause analysis, identifying design and manufacturing flaws, eliminating fraudulent claims and claim processes
CEO’s office Management Dashboards The overall health of the company at fingertips: production quantity, quality, inventory, risk, profitability, costs, etc.

These common pain points businesses face can be transformed into growth opportunities through data analytics as part of the larger digital transformation journey.

Also Read: Digital transformation for SMEs, Part 2: Understanding its maturity cycle

While it may be overwhelming to cover all areas, starting with one or two key areas by prioritizing will contribute towards more efficient use of resources, risk management and better return on investment.

Stay tuned for our fourth and final article in this series. With the charting and planning in place, we tackle the implementation of digital transformation into the organization’s structure and processes.

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: wrightstudio

The post Digital transformation for SMEs, Part 3: Data analytics in the enterprise appeared first on e27.

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