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How companies can increase their productivity by 25 per cent - the easy way

(Image credit: Image Credit: Andrey_Popov / Shutterstock)

Overworked, overstressed, and overloaded – with data. Life today isn't easy for workers on any level of an organisation. Companies are cutting costs wherever they can, and that means fewer employees and fewer resources. But there's more work than ever – and as a result, companies need to be more productive to remain competitive, and employees are busier than ever.

One reason they're so busy is because there is so much data. In fact there's so much data that employees in large organisations need to wade through that they are spending no less than a quarter of their time just searching for it. Eliminate that search time and you automatically increase productivity by 25 per cent

But it's even worse than that; employees, too, are less motivated to work because of the frustrations involved in getting their work done. A poll of employees by UK firm Teleware said that over a third of employees were very frustrated over wasting “a lot” of their working day trying to resolve an issue with missing or forgotten information. Time spent searching for data is time that cannot be used to apply that data to solving business issues.

Add that frustration to the two hours a day lost to searching for data, and you have a situation where employee turnover, lost accounts, and financial losses become “inevitable.” But it's not; and now that we know what the problem is, we can do something about it.

How did this situation come about? Data now comes in from many sources. To conduct their work, employees need to access databases, social media sources, email accounts, servers, etc. The more sources, the more places employees have to search in order to track down data for their project, presentation, sales pitch, etc.

For example, sales teams at a company that sells tech products to large clients will need to keep track of a large number of details in order to make successful sales pitches. Emails and documentation from clients, files from design and engineering listing the technical specifics of the products, regulatory documents that affect the sale, emails or documents from Finance that could impact the deal, etc. That could easily take two hours a day, or more, to round up. So what can, or should, companies do about it? There are several solutions, each with their plusses and minuses:

Consolidation to reduce waste and information complexity: To ensure smooth operations, procedures have to be “smooth.” That means implementing a logical, repeatable method of dealing with data that doesn't require customisation for each instance. That could include standardising assets and procedures for handling data – what scripts to use, where new data is to be stored – bringing structure and logic to data management. Standardising procedures entails standardising access as well – bringing all the data sources together in a single network, or indeed uploading data to a cloud repository.

For standard data searches – forms, standard presentations, etc. - this system would work just fine. If the company has special needs, such as a high degree of customisation for each client, this approach might leave something to be desired.

Eliminate inefficiencies

Enterprise Search: Without context, content is worthless – and enterprise search seeks to give context to data by defining its characteristics, indexing it, and classifying it into categories Given context, internal search engines or scripts can refer to common, accepted terms used in the organisation. Even if the data that has been uploaded uses terminology or features that are not generally used in the organisation, an enterprise search system will put that data into context.

For companies that have the resources to do this, enterprise search provides a great solution. But getting there from here isn't easy; terminology needs to be common to all applications, and data has to be continually parsed by search scripts – which need to be constantly updated to account for new definitions, sources, and contexts. The system works, but it requires a huge amount of backend tech to work properly. Because of the enormity of the effort, many companies rely on an outside company, like Microsoft, to do their indexing and search (via Office 365) – but there are some tasks that MS is not up to, according to experts.

AI: Another alternative is using an AI-based virtual container system to build directories of files, emails, web links, and anything else related to a project. Similar to enterprise search, the AI does the heavy lifting, tracking down that data and present it as an element in the virtual directory, using a hyperlink to the actual file itself. And if the system is equipped with machine-learning capabilities, it could continue to assimilate new information relating to a project as it comes in, based on how data is used, where it comes from, who is using it, etc. Thus our sales team would have the data they need “delivered” to them, instead of having to track it down – and the files and messages remain where they are, in their native states and using their native applications.

While AI could be a solution, it isn't perfect just yet – and a system like this could be expensive for companies, as advanced systems tend to be. Nevertheless, this would make sense for companies with deep pockets.

The solution, then, can come in numerous forms – and it may depend on the size or situation of an organisation. For small companies, custom-written search scripts that parse servers, databases, and email accounts for relevant data could be the answer; for “boutique” firms involved in very high-level, high-security deals, converting all data to a proprietary platform could work best; and for companies that can afford it, AI-based smart search virtual directory systems could be their solution.

The bottom line is to work towards a solution by thinking about the future: Consolidating platforms, reducing shadow IT, streamlining and standardising processes, focusing on making doing the right thing easy for employees. Those rules apply to whatever solution a company chooses, because at the end of the day, the most difficult part of implementing any solution is figuring out how to get people to change the way they work. Any one of these options is better than the 25 per cent-plus time that employees are wasting each day. Doing business is hard enough today; the more inefficiencies and waste we can eliminate, the better for everyone.

Yaacov Cohen, CEO of (opens in new tab)

Yaacov Cohen is co-founder & CEO of A driving force for humanizing technology through people-first work environments, he believes technology should work for people, not the other way around.