How manual reporting jeopardises your profitability and performance

How manual reporting jeopardises your profitability and performance

manual reporting

For most large companies, manually generating reports to evaluate operational performance and service deliveries can take weeks, if not months. How much time do you spend fiddling with spreadsheets, moving data from one place to another just to build up a static and isolated report?

Manual reporting introduces further problems of which you may not be aware. Read on to find out how your manual reporting system jeopardises your business.

Four ways manual reporting impacts businesses

Data silos

In many business environments, data is gathered from multiple departments and sources. For the business to make decisions based on this data, it needs to be organised and communicated so that everyone involved understands what it means. Manual reporting gathers all relevant data from various sources and then relies on staff to analyse the information before creating a report.

The problem here is data silos. Each area works on reports that are not easily or fully accessible by other departments, so the information available to one department is unavailable or requires significant work to be shared with others. Data silos may not seem like a big deal, but this creates inconsistencies in data that may overlap across silos, leading to a deterioration of data quality, unreliable insight and delayed action greatly affecting your operations performance. This leads to the next key issue found with the manual reporting process.

Multiple versions of the truth

One of the easiest ways for errors to find their way into your data is by creating multiple versions of the truth.

Imagine you create a P&L report. You then pass this on to relevant co-workers to review and make adjustments. They send the report back to you to review and approve. You then pass it on to your superior who reviews and sends it back. You create the final version and send it to your superior, who then reviews and presents based on this report.

What happens if one person sends the wrong version? Or realises after the second or third review they made an error? Then there are even more versions of the same report in existence.

This is how manual reporting severely compromises your data integrity and adds unnecessary delays to the decision-making process.

The human factor

Manual reporting is prone to human error and bias. As the amount of data available grows exponentially, it becomes impossible for humans to handle it all. At some point, you’ll have to start manually filtering out what’s relevant and what isn’t, which is a dangerous path to take.

As data is gathered from multiple software sources like Salesforce, SAP, Xero, Netsuite, and others, plus devices like IoT sensors, then finally put into Excel spreadsheets and PowerPoint presentations – there are many touchpoints that create a huge concern for data integrity.

If you’ve ever tried typing numbers from an online report into Excel, you’ll know that mistyping or creating a formula error is all too easy – and not always noticed. One study found that when manually entering data into spreadsheets, the probability of an error was between 18% and 40%. The effects of even one error can result in bad decisions made from faulty data.

Time-consuming

Without question, manual reporting is labour-intensive and time-consuming. It takes hours each week to manually gather data to compile a simple P&L or service delivery report. It’s estimated the average worker spends 2.5 hours per day – that’s 30% of their workday – searching for information.

This not only hinders your leaders’ ability to make timely and effective decisions but prevents you from building confidence in your insights. It takes time to confirm each data insight against reports and seek direction from management. By the time a decision is made, the data is no longer current.

In today’s world, every minute counts. Manual reporting prevents you from making real-time decisions to act on current information. It focuses more time and attention on data validation than on data analysis. Huge amounts of time spent gathering information, costing your organsiation a great deal of time and resources to act on outdated insights. 

How Metro Trains Sydney removed manual reporting

Bring your organisation up-to-date with Decision Intelligence

Manual reporting is becoming a relic of the past. It is time-consuming, inefficient, inaccurate and expensive. It also lacks the scalability that modern businesses need to grow today.

Decision Intelligence propels your organisation into the future by building a solid data foundation that supports more effective insights and outcomes. Rather than spending weeks working on performance analysis, you can instantly see your operation in a centralised visual dashboard that displays only the information your need. 

The best part is that you don’t have to be a data expert – that’s what we are for. The Toustone team is passionate about helping every organisation become more efficient and productive by maximising their data. We can work with you to develop a solid data foundation and apply a custom Decision Intelligence solution to enhance your transportation performance. 

Contact Toustone today to get your transportation business on a speedy track to greater efficiency.

Data-driven: What is it and why does it matter?

Data-driven: What is it and why does it matter?

Smart Farm: What you need to know

We constantly use data to make decisions in our everyday lives. What products we buy, which route we choose to take to our destinations, the content we read and the conclusions we draw from it.

Yet in business, too many decisions are made based on gut feeling. A recent global survey reported that 58% of respondents say their companies base at least half of their decisions on gut feeling or experience rather than data and facts. While we may have developed great instincts over time, our opinions can be biased, influenced by emotion and often fail to assess the entire picture.

This is where the term “data-driven” comes into play. In a data-driven organisation, strategies are developed based on facts. The guesswork and emotional aspect of decision-making is removed as insights from data present clear ways to move forward in every area of the business

Why does being “data-driven” matter?

You need to make a marketing decision. You open a spreadsheet with historic sales figures, another with past campaign results and spend five minutes searching for the most up-to-date financial report. You find three different versions – which one is correct? Which one did your staff use? Can the numbers be relied on? Frustrated, you decide to go with your gut. If it’s worked before, it will work now, right?

Imagine instead that all of the data you need is presented in automated current reports. With a few clicks, you can dig deep into the numbers and understand the story behind them. Actionable insights are presented based on the data, guiding your decisions. There is no guesswork. Your entire team works from the same source of data, from IT through to operations.

This is what a data-driven organisation looks like. There is one single source of truth instead of multiple versions. The risk of making decisions based on outdated information is eliminated. Data is accessible, at your fingertips, with insights generated for you.

Data is utilised to lead the decision-making process. The data-driven organisation has a mentality of constant improvement. Insights allow you to quickly make the best decisions for the business and predict future trends so you stay ahead of the game.

Smart Farm: What you need to know

Getting started with data

To be an effective data-driven organisation, a solid data foundation is critical. If the data you start with is inaccurate, how can you expect to make the best decisions?

A Decision Intelligence solution starts with building a data foundation from quality data. The data is then mapped and stored in a data warehouse where queries are run to build automated reports. Reports are delivered directly to the user, and can be accessed anytime from anywhere with an internet connection.

Toustone sets this all up for you with minimal disruption to operations. You don’t have to understand how it all works. We’ll work with you to understand your organisation’s needs and provide a solution.

Empowering your staff with reliable, accessible data means everyone can make confident, consistent decisions. You control who has access to what, so your staff only sees what they need to see. This protects the security of your data while allowing each department to focus on what is relevant to them.

Any organisation stands to benefit from being data-driven. Every department can rely on data, from finance to customer service, to make the best decisions.

To get your business started on the path to being data-driven, contact our team at Toustone today.

Five Steps to Increase Customer Engagement with DI

Five Steps to Increase Customer Engagement with DI

Leverage BI

You have the power at your fingertips to turn your customers into brand promoters. Using data, you can get into your customers’ heads and understand what they truly want and expect. Therefor, you can then deliver a personalised experience to maximise engagement and give them a reason to return. Resulting in happy, loyal customers that translate into increased sales and more word of mouth advertising.

There is more data available to you than ever before. Diving into this data can give vital insights into your customers to improve every interaction and increase engagement – if it’s utilised properly. A Decision Intelligence (DI) solution catered to your organisation’s needs can deliver everything you need to increase your customer engagement.

Here are our 5 steps to increasing your customer engagement with a DI solution.

1. Get a deeper insight into consumers

Data can be used to build accurate customer profiles. Who is your customer? Where do they live, work, recreate? What is it they want from their experience with you? Customer profiles allow you to really understand your customer so you can anticipate their needs and exceed their expectations.

With a DI solution, your focus changes from hitting sales targets to delivering a customised experience to each customer. People don’t want to be sold to. They don’t want to hear your pitch. They want to be able to see the value you offer and decide for themselves to do business with you. A personalised experience, using targeted advertising and highlighting products suited to them based on their search and purchase history, along with a human touch is key. A DI solution can make it easy for you to do so.

2. Identify what is and isn’t working

Using data from on-site behaviour allows you to track customers actions. What is most engaging? What brings them back? At what point are they leaving your site? Tracking your customers’ habits gives you the information you need to make your site more appealing and work better for you.

A DI solution will show you these insights in real-time, so you can take immediate action to improve your marketing. In an instant you can remove what’s not working and make changes to focus on what is. Patterns you would not have spotted yourself will be identified for you. Changing trends will be made clear so you can stay on top of them and ahead of the game. Through quick insights into what is working for your customers you can increase retention and watch your sales climb.

Leverage BI

3. Combine all data into one place with visual dashboards

A picture is worth a thousand words. Visual dashboards organise a large amount of data and present it in an easy-to-understand format that goes far beyond numbers on a page – and it’s all compiled into one place.

Any time your customer makes a purchase, clicks an ad, contacts your business via phone or email, comments on your Facebook page or in any other way has an interaction with your business, it is all captured in one place. This gives your staff the tools they need to provide an efficient, fast and satisfying experience for your customer.

No more gathering information from multiple sources – a DI solution will gather it into one place for you, empowering you to deliver a higher level of service.

4. Predict customer behaviour with analytics

DI gives you the ability to predict your customer’s future behaviours before they occur! Using past and current patterns with statistical data and Machine Learning, predictive analytics allow you to fine-tune your marketing, customer service and sales approaches to the exact point your customer is at in their cycle with you.

For instance, do you find that your customers start out strong in their relationship with you but gradually interact less and less, until they drift away? Predictive analytics will identify these patterns and alert you to the appropriate time to intervene to retain your customer.

Upcoming trends and shifts in your industry are identifiable with predictive analytics. This gives you a major advantage in jumping on trends and capturing customers that your competitors are missing.

5. Depend on your people to get it done

Any DI solution depends on the people who use it to make it work. By integrating data into your organisational culture you can ensure that everyone works from the same data source with their targets set on shared goals. A data-driven culture will break down silos that separate one department from another to allow for more teamwork and higher performance.

A DI solution can also deliver employee performance metrics allowing your staff to self-monitor their performance. They are empowered to enhance their potential without having to wait for a performance review.

Don’t just take our word for it

We recently worked with mobile engagement solutions provider Plexure in partnership with Yellowfin to help them deliver improved personalised customer engagement. You can read the case study or view our recent webinar with Will Hunt, Product Manager of Analytics & AI at Plexure, where he talks about how the solution worked for them and how they scaled to users in 60 countries in a couple of months.

At Toustone, we are committed to helping every organisation improve through the use of data. Get in touch today to see how we can provide a DI solution that will enhance your business and help you grow into the future.

Predicting Absenteeism with Data

Predicting Absenteeism with Data

Meat Processing

Absenteeism affects every business operation. If someone isn’t there to do their job, the tasks are either delayed or another person has to be found to fill in. Direct costs include the expense of paying out sick leave plus replacement staff. Indirect costs are seen in delays of work and the effect of the absence on coworkers or supervisors. Costs begin to add up and affect the bottom line. In Australia, the annual cost of absenteeism to the Australian economy is estimated at $44 billion per year.

But, through the use of existing data, absenteeism can be predicted and potentially prevented.

In our last article, we went over the compounding effect of data and it’s three components: hindsight, insight and foresight. To sum up, as the use of your data is optimised, you move from assessing what happened and why to predicting what will happen. You are able to see what actions you can take to ensure a favourable outcome. Your existing data is optimised and gives you the ability to make better decisions and better decisions lead to better business.

Absenteeism is one key area that we can assess with the compounding effect of data to better understand why it happens and prevent it from happening in future, resulting in a significant reduction in cost.

Predicting absenteeism in the Meat Industry

Labour-intensive operations where consistent staffing is key to keeping up with output are most affected by absenteeism. Australia’s Meat Industry employs over 32,000 people and is a $21 billion-dollar industry. An analysis done by the Australian Meat Processor Corporation found that labour makes up 58% of the operating cost for beef processors. With absenteeism a major issue in the meat industry and labour costs comprising a significant portion of the cost of meat, processors should be particularly motivated to control absenteeism.

By utilising the compounding effects of data, absenteeism can be accurately forecasted and potentially prevented to increase efficiency and reduce cost.

First, by applying Descriptive Analytics to existing data we can extrapolate the rates and costs of absenteeism. This is the hindsight step – looking at what happened. It’s a basic assessment of how often and where absenteeism is occurring and the associated costs.

Then by using Diagnostic Analytics we uncover why it occurred – this is the insight component. Illness or injury, stress, family issues, transport issues and even employee morale can all be reasons for absenteeism. Analysis of data can pinpoint departments, divisions or geographic locations, all creating a picture of the reasons behind the occurrence.

Finally, we head into the foresight component of the compounding effects of data, where we apply Predictive Analytics to predict when absenteeism will occur, based on what we have already learned about the rates and the reasons. The ability to forecast when it occurs means you now have the ability to take action to prevent it from occurring.

Preventing absenteeism has a significant effect on labour cost while increasing production and keeping customers satisfied. Australia’s meat industry would see a major benefit by using their existing data in the most effective way through the application of Decision Intelligence solution.

Meat Processing

Getting started with data

At Toustone, we are dedicated to help businesses make effective use of their existing data in order to grow. Our reporting solution delivers simple, automated dashboard reports identifying trends, costs, and insights, enabling you to make the best decisions without wasting your time on gathering and analyzing data.

The Compounding Effect of Data

The Compounding Effect of Data

Smart Farm: What you need to know

Data-driven companies have the advantage of relying on sound data in every aspect of the business. Rather than focusing on continually gathering more data, they take the data they have and use it in novel ways to drive decision-making. The compounding effect of data increases the value of the data you already have and simplifies the process of optimising your data.

The compounding effect has three parts

  1. Hindsight
  2. Insight
  3. Foresight

Hindsight is the stage where you are building your data foundation. It involves looking at descriptive analytics and analysing what has already happened.

Insight is the practice of using diagnostic analytics to understand why it happened.

Foresight takes your data a step further, using predictive and prescriptive analytics to predict what will happen and how you can make it happen.

The result goes beyond using data to understand what happened and why to using your data to create desirable outcomes.

Application to Human Resources

Traditionally, Human Resources (HR) have been seen as a people-oriented industry. They spend a significant amount of time dealing with staff appraisals, recruitment, satisfaction surveys, and management issues. Today, data can transform HR to an area that delivers insights that have a significant impact on an organisation’s overall performance.

Utilising Data in HR can:

  • Forecast and minimise absenteeism
  • Optimise recruitment tactics
  • Identify how best to keep employees happy
  • Understand the employee lifecycle – know when someone is about to leave
  • Track payroll and compensation
  • Enhance employee COVID tracking

When HR is data-driven, it results in making better decisions that add value to the business. Less time is wasted on recruiting and training. The workplace can be optimised for employee satisfaction. The heavy cost of absenteeism can be reduced.

These days, perhaps most importantly: COVID can be tracked to minimise the spread and impact on your workforce.

Smart Farm: What you need to know

Example

It was identified early on that the meat industry was a high-risk area for COVID transmission. In Melbourne, Cedar Meats was closed for six weeks due to an outbreak among staff – a cost no business wants to face. How could HR data help prevent this?

Even when strict COVID protocols are enforced in the workplace, workers are coming into contact on the way to and from work. Within the meat industry, it’s common for staff to carpool to work together as many locations are in remote areas.

Developments in Bluetooth tracking technology mean an alert can be generated when employees come in close proximity. This data can be used to track who may have been in close contact with someone who tests positive for COVID and speed up the isolation and testing procedures.

To manage this data, a well-supported data environment and system are required to assess the data, draw meaning from it and generate reports that can be acted on in real-time. It may be that changes in shift capacity, start and finish times, and break times could decrease employee contact. Automated insights can assess the data as to what has happened and why and predict future occurrences. In this way, data can be a major force for containing COVID outbreaks.

Smart Farm: What you need to know

Are you getting the most out of your data?

The above example is just one of many ways that the use of data can advance your HR practices, but this is not limited to HR, any department can improve their efficiency to help their organisation grow, from HR to sales to operations. Check out some of our other articles that talk about how data can reduce absenteeism and enhance productivity.

Top 5 Data & Analytic Gartner Trends

Top 5 Data & Analytic Gartner Trends

Smart Farm: What you need to know

Data and artificial intelligence (AI) have taken on massive roles in managing the aftermath of the Covid-19 crisis. What does this mean for data and analytics as we prepare to face a post-pandemic reset? To help you get ready for what’s coming next, we’ve selected five of Gartner’s Top Trends for 2020 to identify areas to focus on:

  1. Smarter, faster, more responsible AI
  2. The decline of the dashboard
  3. Decision Intelligence
  4. The Cloud is a given
  5. Data marketplaces and exchanges

1. Smarter, faster, more responsible AI

Gartner predicts that by the end of 2024, 75% of enterprises will have made the move to operationalising AI. No more development and control – it’s time to rely on the technology.

Machine learning and natural language processing deliver vital insights and predictions, so increasing investment in these aspects of AI technology is key. Human-machine collaboration and trust will be enhanced by model transparency – if you see it, you can believe it – driving efficient decisions.

AI technology is available to you now. Yellowfin Signals monitors and analyzes your data and notifies you of significant events. The relationship created between user and technology allows for faster and more effective decisions. Steering toward a reliance on AI now will help you make better decisions in a post-pandemic world.

Implementing AI on top of a foundation of reliable data is the next step to keeping pace with rapid and informed insights. Are you ready?

2. The decline of the dashboard

The second trend we pulled from the Gartner report to help you prepare for the unprecedented shift we are experiencing in the wake of Covid-19 is the decline of the dashboard.

If you just got used to dashboard reporting, don’t worry. It’s not going away, it’s just getting better.

While dashboards revolutionised the way we view data, the standard point-and-click exploration of predefined dashboards will shift to the next level – automated delivery of insights in an easy-to-understand format.

Data reports will be replaced with data stories. It goes a step beyond reporting as the insights are generated for you. And you don’t have to be a data scientist to understand a story. This saves an incredible amount of time that would have been spent on analysis.

So who sees the stories? A few weeks ago I mentioned sharing your data with the right people was a key step in getting the most out of your data. Automated insights builds on that as relevant data stories stream to each user based on their context, role or use.

The right people get the right data pre-packaged as insights. Their job then becomes acting on those insights, instead of developing them – and more time spent on action yields faster results.

3. Decision Intelligence

The third trend has to do with Decision Intelligence. Gartner predicts that 33% of larger organisations will be practising a higher level of decision intelligence by 2023.

What does this mean? Faster, better decisions based on data, including automated decision management and modelling technology.

Decision Intelligence brings together several disciplines to give a framework for making high-level decisions using multiple logical and mathematical techniques. Automating this process – or at the least, documenting and auditing – allows for faster execution, monitoring and analysis of AI and ML supported decisions.

In this way, data-based decision-making swiftly drives the business processes and the processes are monitored to keep in line with the business strategy. The result? Better outcomes for the business.

While machine learning drives better decisions, it still requires a human aspect to be the decision-maker by initiating the actions based on decisions. By exploring Decision Intelligence now your team can remain ahead of the game in the uncertain days ahead.

Smart Farm: What you need to know

4. The Cloud is a given

Remember dial-up internet? It’s hard to imagine where the world would be if we hadn’t progressed from those days.

Soon we’ll be saying, “Remember life before the cloud?”

By 2022, the cloud will be essential for 90% of data and analytics innovation, according to Gartner’s latest trends. As data and AI take on more of a role in the unprecedented times we are living in, the speed of cloud services will be necessary to stay competitive.

We currently see companies benefit from cloud services with increased efficiency, security and clarity. Data can be automated and scalable. Increasing data storage with manual housing can take 6-9 months, while with the cloud it takes mere seconds. Building your data foundation in the cloud drives efficiency in reporting, so you can spend more time acting on insights instead of building them.

The good news is that you can shift to the cloud in seconds with Toustone proven technology partnered with AWS. We’re experts at getting the most out of your #data, so we can guide you from step one to get your organisation up to speed. We make the transition easy so you can focus on what’s ahead while the pre-cloud days become a hazy memory.

Have you adopted the cloud? Check out our Hosting Solution!

5. Data Marketplaces and Exchanges

Picture a marketplace – a collection of stalls selling everything from food to clothing to handmade goods. It’s convenient for both buyers and sellers, bringing goods to one location keeps costs low and makes it easy for buyers to see what’s available.

A data marketplace has similar advantages – bringing together multiple buyers and sellers of data in one cloud-based location reduces costs and showcases everything available.

Number five in our Top 5 Gartner Trends is a shift toward data marketplaces. In two years, 35% of large organisations will be either sellers or buyers of data from online data marketplaces. As more businesses monetise their data, the amount of available data grows exponentially.

The availability of third-party datasets can be a boon to businesses by providing centralised access to multiple providers on one platform and reducing costs. The improved insights drive real results.

But before you dive in, make sure you know how to combine your internal data warehouse with these outside data sources. It’s a powerful force for driving insights but you have to maintain your focus and not get distracted by extra data – there’s a lot of it out there.

Are you ready to take advantage of third-party data to improve your insights?