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.
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