Nov 24th 2015

Keep it real!

innovate

Businesses are starting to grapple with using analytics technology as a service. Different people in each business have different expectations of the technology – ranging from those who are fearful of what analytics might highlight about their own performance, to those C-suite executives who don’t understand what predictive analytics can do for the business (“I already know what I need to know” etc.). Some even think analytics can replace people. All of these views are based on misconceptions.

 

Analytics is about giving your people the tools and data to perform better and make more informed decisions.

 

However, analytics alone isn’t going to transform any business. It won’t decide your business strategy for you. Human involvement and interaction is key.

 

Outsourcing analysis

 

What are the benefits of analytical software services? Well, like other outsourced services, the business saves money on buying often expensive IT kit and software tools for analysing data.

 

One retailer we know had about 50 people working to improve data from its ERP system on the performance of its business. The ERP system was spitting out reports that were of little value, on tools that were inflexible and hard to change, and to timeframes that were unacceptable to the business, areas that can be amended through an outsourced data analytics/business intelligence service.

 

Also, the supplier can expand the technology’s capacity at short notice to cope with surges in demand for a business’s product or service. Or reduce capacity when your business is quieter. You only pay for the computing power you use.

 

Smarter Data

 

Companies are also using data analytics services to increase efficiency. One logistics business, for example, did activity-based costing to analyse the profitability of its many contracts. Before using data analytics, the company didn’t have an overview of its contract costs. So many people and processes were involved and the different stages in delivering the parcel, it obscured the costs of each contract.

 

By scrapping some contracts and asking more money from other contracts (where it was under-charging customers) the company recouped the cost of the three-month project in one week thanks to data analytics.

 

It’s not just about big data. Small details can make a big difference to a company’s performance. Another retail business analysed its fleet of vehicles using an outsourced data analytics service.

 

It found that many of its trucks were not turning right during their deliveries, as doing so often involved crossing a busy road which was more hassle and more stressful. Instead the drivers took lengthy de-tours, which increased fuel costs and journey times. The company saved thousands of pounds a month in fuel costs by encouraging its drivers to drive differently.

 

Predictive Analytics

 

But analytics can do more. Much more. Now, alongside analytics as a service, you may have heard the term ‘predictive analytics’. The idea is that companies use all their data (sales, running costs, customer satisfaction etc. from ERP, CRM and other back-office IT systems) to predict their performance.

 

But there is one key component required to make predictive analytics work: human involvement and intuition. It’s not about replacing the sales director or IT staff with clever software.

 

Analytics alone isn’t able to transform a business or decide its strategy. It’s there to add a string to a sales director’s and company’s bow and underpin their decisions.

 

We’ve put together some tips for getting good value from analytics technology:

 

One, have a good understanding about your business (sales, profits, customer satisfaction etc.) before comparing its performance to rivals.

 

Two, start your project slowly by focusing on your most valuable customer data first, before widening it to collect and analyse other data. Add new functions to the data analysis every couple of months. The main reason analytics projects fail is because they’re trying to do too much too soon.

 

Three, share data across your business. Don’t let IT, sales or finance keep their data in departmental silos. Sharing data will help produce ideas on how to do things differently and improve the business performance.

 

Four, measure the return on investment from your analytics after one year. It may take a while to work out any links between improved performance and data analysis.

 

Conclusion

 

Analytics is advancing fast, helped by cloud technology and demand from businesses for technology that can help make sense of their vast data and improve their performance. But to harness the full power of analytics, companies need to refute misconceptions of the technology: that it will replace staff, or that it’s 100% accurate on its own.

 

It’s time to give business intelligence back to the business. To learn more about how we can help you make the most of business intelligence and big data analytics, get in touch with us today.

 

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