How Small Businesses Can Gain a Competitive Advantage From Big Data

The term ‘Big Data’ has been around for a while now and it is more than likely that some of your competitors have been using big data to improve customer relationships, enhance marketing operations, streamline financial decision making and much more. Although there is a common belief that this is something reserved for large businesses to utilise, there are many reasons why the big data concept is applicable to small businesses.

“Technically speaking, big data is a reference to data sets too large and complex for companies to manage within their traditional IT systems. But a look past the technical jargon will reveal that big data is about opportunity – the opportunity to learn from your company’s data in order to make smarter business decisions.”Joanna Schloss, Business Intelligence and Analytics Expert, Dell Software

Pinpointing relevant big data

Many businesses focus on acquiring a large volume of data and this can be misleading. Whilst some situations might require vast amounts of information, there are many ways in which having the right data is the most important factor. For example, businesses that have perishable goods may want to receive alerts when items are nearing their sell by date. If businesses don’t receive these alerts they risk wasting stock.

Small businesses deploy a variety of solutions to meet their needs, such as accounting software, CRM Systems, ERP systems, eCommerce, with each of them collecting different data. In this regard, small businesses already have a wealth of useful data at their fingertips. The information captured from day-to-day operations can add significant value, but it has likely sat untouched without employees making good use of it.
“Believe it or not, if your company has been operating for a year or more, you likely have a ton of “Big Data” sitting in your company records.”Kevin Tulley, Consultant, Smart Data Collective
If this data remains buried in your business systems, it may as well not exist. This information will only be of value when it is both accessible and communicated to the right people at the right time. This is not always plain sailing. Information can be time-consuming to collect, difficult to locate and tricky to deliver concisely for decision making purposes. In many instances, manually monitoring systems for insights will not only be a drain on resources but inherently difficult to distribute accurate real-time information.

How can big data be used effectively and efficiently?

As we’ve established, business data is pouring into organisations from a wide variety of channels and includes useful insight into customers, prospects, products, inventory, finances and employees. The key to successfully utilising your own big data is to be entirely focussed in your approach to the information you utilise. It’s not the volume of data you have but its accuracy and how it is used. Notifications and alerts can be delivered in an appropriate format to leverage the data in systems already in place within an organisation. Furthermore, being a small business means that you’re in the ideal position to action insights and deploy solutions swiftly.
“Even the most potent insights are valueless if your business is not agile enough to act on them in a timely fashion. Small business have the advantage of agility, making it perfectly suited to act on data-derived insights with speed and efficiency.”Howard Baldwin, Community Editor for Data Driven Business at Forbes
To gain a competitive advantage it’s key to determine which critical segments of data are required, and how it can be extracted and distributed accordingly – internally or externally. The business decisions made from receiving this information can have a significant effect on the organisation’s ability to satisfy customers, reduce costs, improve productivity or mitigate risks. On the other hand, the consequences of not getting that information can be disastrous and impact your business negatively. For example, incorrect customer details such as a wrong address can result in an unhappy customer not receiving their order and, for you, it’s wasted money on postage and returns.

What would be helpful to know from the data sitting in my resources?

Whilst the following examples demonstrate ways that notifications can be utilised, there are endless possibilities available to you with different goals in mind. For instance, data management alerts for cleansing and integrity, critical notifications for problem solving, informative alerts for decision making and real-time status notifications for key knowledge and understanding.

Accounts and Credit Control

  • Alert staff when key activities occur in finance / ERP systems:
    • Customers put on hold
    • Orders waiting for manual release
    • Credit limit change requested
  • Warn about unallocated invoices or when invoice is allocated to the wrong nominal code
  • Alert if goods are shipped but no invoice is raised
  • Monitoring of aged debt with alerts to Directors at key milestones

Sales

  • Chasing sales people who have not submitted activity reports or other documents
  • Alerting sales people when their activity levels fall below pre-set thresholds
  • Notification to a sales person when another person, for example a member of the customer service team, speaks to one of their customers
  • Notification to sales people when their customers place technical support calls or these are escalated
  • Alerting Account Managers when their key customers follow links in marketing emails

Human Resources and Payroll

  • Holiday reminders – encouraging staff to use their holidays evenly throughout the year
  • Monitoring of time and attendance records and alerting when anomalies are found such as regular lateness or excessive overtime
  • Alerting directors with details of how much overtime people are working
  • Sickness monitoring – alerts sent if an employee has an abnormally high number of sick days
  • Probation period monitoring – generating alerts to the relevant managers when an

Warehouse, Stock Control and Distribution

  • Stock level warnings – too high, too low
  • Slow moving stock identification and short shelf life stock warnings
  • Warnings of large stock movements due
  • Notification when back-ordered stock has been received
  • Alert if excessive time is taken to pick an order
  • Goods dispatched notifications sent to customers
  • Warning when an item is receipted into stock with margin that is too low or has been receipted at a buy price that is different to the expected cost price
  • Alerts showing goods due in that have not turned up on time
  • Service reminders on warehouse equipment generated automatically
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