Are you missing the low-hanging fruit on your data tree?

You could be closer to becoming a data-driven business than you think. That’s because chances are, you’re already generating data and you just need to know where to find it, how to aggregate it, and how to use it to create real value within your business. Start with the quick wins and there will be many ways to build on them and transform your firm with assets you already have

Many companies are missing out on the low-hanging fruit because they don’t realise how much data they already have. The data they currently do use, is mostly to monitor historic activity as opposed to powering future business performance and decisions. The problem is that the inability to use data is causing firms to miss out on vital insights, and therefore new business opportunities.

So if businesses have access to all this data, where exactly is it? Well that’s the problem. It’s everywhere. It’s sat in different places all over the business. It’s fragmented among many departments, databases and line-of-business applications. And even for those who know of its existence, it’s incredibly frustrating because they can’t get it all in one place, which is the biggest challenge.

Unbelievably, we live in a world where only five percent of corporate data has been successfully analysed to drive business value. That’s a staggering 95 percent that is left uncovered in silos connected to solitary devices or applications, organisational silos in departments or subsidiaries with a single view on the value of that data, or cultural silos where a lack of innovation is hindering the value that data could bring.

Businesses are swimming in data but it’s only when you have it all under management that you can start to get a return on the data.

Data, data everywhere

No one wants to be the next Blockbuster or Kodak but the truth is, the health of a company’s present and indeed future success lies in their ability to use data to enhance their business. We showcased some of these examples at this year’s Smart IoT London where we spoke and showed our latest IoT analytics, machine intelligence, AI, and augmented analytics demos.

Often, when people hear the word data, they think of the information being pulled from the sensors on their machines. In the IoT era, this type of data is exploding as more endpoints appear in workplaces around the world, and thankfully, it’s getting cheaper to store this data than it used to be.

But there’s so much more data under your nose that could prove really insightful if combined with data from elsewhere. There are the traditional datasets from systems of record and quote to invoice systems. Then there are CRM data, maintenance schedules, enterprise resource planning and logistics information and social media data. All of it is sitting somewhere within the four walls of your business waiting to be used to its full potential.

This is the stuff data scientists the data-innovators thrive on. A rich pool of information from a variety of sources is what forms the basis of any high performing algorithm that goes on to create innovative business models and differentiated solutions. However, the more data that is available, the more difficult it is to collect it, and the more likely that insights will be missed as a result.

So when a company enlists the services of a data scientist, too much of their time is spent carrying out the basic data collection and preparation tasks instead of exploiting the value of the data. Every company should be looking to get the best return on their data. Automation will help here. According to Gartner, 40 percent of data science tasks will be automated. But another vital element is being able to identify what data you are already generating within your business to enable the data scientist to be more productive with higher value tasks.

Once that’s done, get it into the hands of as many data-driven innovators as possible including the data scientists and the citizen data scientists using modern tools and solutions that can both centralise and orchestrate data. That way, the data is in one place but can be used in a way that suits the business and lends itself to being used by the data-innovators within the business.

Knowledge is power

Widening out the field even further, you’ll see that the precious insights you have aren’t just coming from machines and internal systems, they’re also coming from people. But these are insights that you could lose if those people leave the company. The average staff turnover rate in the UK is 15 percent according to Monster. If your business were to lose that amount of people over the next year, and those people were senior tenured staff with a lot of company experience, how hard would it hit?

You can make the most of the data held by these people by taking steps to create digital twins whereby a digital representation of a physical asset is created. Although the term digital twin is usually used with computing assets, you can also create a digital representation of knowledge. If you can start integrating all the data points associated with their workflows and knowledge, you can then extract the knowledge they hold and enable it to live on after they have left the company.

What’s more, with the inclusion of automation, the processes based on potentially years of manual task data could be done more easily than ever.

Bringing it all together

If you’re looking to get started on this data journey, where should you begin? The first step is to start with a problem. Is there a part of your business where you are losing money hand over fist and do you think there’s a reason behind it? Your problem should be a specific one because it’s near impossible to fix everything at once.

The next step is to see if data can be part of the solution. That’s where you start to look at all the data sources you have available to your business. You should carry out this step before you bring in the data experts to ensure you can make the best use of their expertise.

You should also be systematic. Don’t let a provider try to fix an issue without showing their workings. They should show their methodology and prove it, enabling your company to see the link between the data you are using and how it was able to help solve the problem. If you have success with one problem, you can then go to the next step and use the data in another way to help somewhere else.

It’s vital that businesses become aware of the obvious starting points they have with the data that’s already around them and use the tools available from the leading companies to centralise the data.

Data analytics is a digital asset like no other asset: it never depletes, never wears out and the same data and analytics can be used across an infinite amount of use cases. Organisations have no other assets on their books that look or behave like data. If we can help organisations be more effective at realising the economic value of their data then we can better help the data-innovators transform and modernise their business.

• Jonathan Bowl, VP & General Manager – Big Data Analytics & IOT at Hitachi Vantara