Virtual Reality: The Next Step for Business Intelligence

Everything is being virtual realit-ified – from product development through to buying clothes.  And it’s now being seen as the next step for Business Intelligence and Data Analytics.

Even simple data visualisation tools are now enabling businesses to make sense of their data – which often runs to thousands of lines of spreadsheet data.  It’s impossible to get a handle on trends and patterns when data is represented in rows, and too big to fit on one screen.

But when turned into graphical representations where trends can be understood in seconds and insights gained in moments, the value of data visualisation becomes clear.

So taking that to the next level and creating a more ‘immersive’ experience is the natural next step.

Plans are underway within data analytics organisations to create applications that enable Data Scientists to literally step inside their data.  They will be able to see the data represented visually in 3D; they can walk around it, stand under it, move it and see it from lots of different angles to better understand what is happening.  They can layer over other data points – over and over to see correlations between information; which is usually limited in a 2D data visualisation tool where it soon gets messy and complex to understand once multiple different data points are overlaid.

Product development departments are already starting to look at how virtual reality can be integrated into their own data workflows, to reduce time spent developing and be able to interact with physical products without the cost or time of developing models first to spot errors.  This offers a great saving opportunity, but also the possibility to explore many ‘what-if’ scenarios that might be too costly to explore with physical products.

 

The world of data is changing

As many businesses now employ Data Scientists, it doesn’t make sense to use the same old tools to do different jobs.  Virtual Reality will provide a new way of visualising and engaging with data.  If we can uncover insights quickly from just seeing a pictorial representation of data, just think what’s possible when you take that into a 3D environment where you can ‘walk through’ information.

The Wall Street Journal has a good example of a Virtual Reality-esque visualisation of the stock market history: http://graphics.wsj.com/3d-nasdaq/.  This helps to give a bit of a flavour of what could be to come – imagine if you could stop on your journey and delve into the detail of a particular year, see a video of reporting at the time in the background while in front of you is a number of visual graphs showing different info that you can move around effortlessly, layering up to gain insights.

It’s a more intuitive and immersive form of data analytics – and I can see how stock markets would benefit from having all of their data in a virtual reality environment that traders use instead of desktop screens.  Or perhaps instead of wall mounted monitors showing tech support graphs, IT technicians will be wearing VR headsets – analysing server capacity and alerts in real-time with virtual reality versions of their remote customer datacentres in front of them to help resolve issues – even when they’re not there in person.

It also offers the opportunity to be more collaborative when analysing and reviewing data analytics – imagine being able to walk your entire Board of Directors through a virtual reality data visualisation of your financial performance to date.  Or perhaps you offer customers the opportunity to understand the data results from their recent Quarterly Business Review with your company via virtual reality headsets instead of emailing over a quick report they probably won’t even open.  Some companies are even developing virtual reality chat assistants to bring an in-person experience to online engagements.

Underneath it all, the aim is to get from complex lines of data through to actionable insights sooner.  And virtual reality certainly looks like it has the power to transform how we engage with data.

 

 

References:

http://fortune.com/2016/09/08/virtual-reality-vr-industries-application-examples/

http://www.forbes.com/sites/forbestechcouncil/2016/07/22/how-virtual-reality-will-impact-businesses-in-the-next-five-years/#7119ea152241

http://pwc.blogs.com/analytics_means_business/2016/08/5-reasons-to-use-virtual-reality-for-data-visualisation-.html

http://www.forbes.com/sites/bernardmarr/2016/05/04/how-vr-will-revolutionize-big-data-visualizations/#2d7e910c4ac5

Why Rio 2016 is both a problem and an opportunity for your data project

The data visualisations that we all see online and on social media are making us more open to using this kind of information at work.

Our daily lives are now drenched in data, delivered to us from our televisions, our computers, and the smartphones in our hands. Charts and tables are commonplace, but the online world and social media have also made infographics a powerful tool for the presentation of this information, especially when coupled with images, animations, video clips and written commentary. This data can come from a huge number and variety of sources, brought in from places all around the world.

A perfect example of this is what we have seen in the coverage of the Rio Olympics. Online news providers have taken great leaps of the imagination in how data can be delivered to us, harnessing the tools at their disposal. The Guardian is a prime example, with their coverage of Great Britain’s cycling success over Australia that saw Sir Bradley Wiggins win his fifth Olympic gold medal (1). The newspaper created an animated version of the race that showed what happened every second of the way, with the reader being able to click through each stage at their own pace.

Not to be left trailing in second place, The New York Times has drawn up an extensive set of data visualisations that shows exactly how well each country has done at each Olympics since the games began (2). The graphics are a brilliant mixture of aesthetics and information, delivering a huge amount of complicated data at a glance.

These high-tech ways of accessing data are becoming everyday experiences for many people, but how does this affect businesses beyond the mass media outlets, and should companies strive to access and make use of these new tools?

There is a danger that if some data analytics projects are at a fairly embryonic stage they could seem outdated by the time they’re implemented. After all, with online trends changing day-by-day, what seemed like a great idea just a few months ago could be old-fashioned by now.

This poses problems for business who are then pushed to keep up with the latest innovations but don’t want to shake-up their operations. However, there is a good chance that your staff are using better, newer technology at home than they have access to when at work.

There are echoes of the BYOD (Bring Your Own Device) phenomenon, where the smartphones that people were buying with their own money were far more advanced than the ones they were being given by their employers. BYOD was a clever way of working around this without companies having to regularly shell out for new phones.

Now your staff will be using the data analytics power of social media such as Twitter and LinkedIn in their personal lives, along with gathering data on themselves with mobile apps such as Run Keeper. It is commonplace to have data at our fingertips, and people will be happy to use equivalent tools at work.

It would be very easy for anyone in the position of running a company that is making use of data visualisations to look at the sort of tools that are being used elsewhere and become despondent at what they have at their disposal. Adopting new technologies can be expensive, and many employers could worry that the changes this can bring to a workplace could have a negative effect.

But what needs to be remembered is that any new data technology that is brought in will probably not be unfamiliar to your colleagues, and may be something they are already using in their everyday lives. With so much technology, and so much data, now available to each and every one of us, that new piece of software that you’re apprehensive about buying may not have the disruptive effect on your team’s way of working that you think, and could give a massive boost to your profit margins.

What’s also very important to remember is that data visualisations are only the endgame of a very long process, one that begins with gathering good quality data itself. While new tools designed to present this data are emerging all the time, the basic foundation that they build upon is information. And if you’re looking at new ways of visualising data then you probably have a good bedrock of this information at your disposal already.

There’s an opportunity here, a massive one, that could see your company pushing itself to the forefront of the way in which data is presented and getting everyone involved in its use, not just data scientists and your IT team.

What’s needed to make the most of this is the realisation that the apps, websites and social media that your staff are using on a daily basis are indicative of a wider acceptance among them of how data now works in our world, and how it touches every aspect of our lives. People are now comfortable with digesting huge amounts of information, and even expect it to be delivered to them. If they do this in their own time, they’ll have no trouble doing it at work.

 

 

Image provided courtesy of Ian Burt

Are You on the Data Offensive or Defence?

Understanding the different types of data positions – data offensive or data defence.

 

Companies are either on the data offensive or data defence – and organisations need to move to being on the offensive to actively take hold of data and make tangible use of it.

There is a huge amount of data that any company will gather over time. This can be deliberate, and be something that you have set out to obtain, or it can be something that simply gathers as a result of the IT systems that we all use.

There are two ways a business can approach this data, and it’s a choice between a position of defence or offensive. One could hold you back, but the other is much more positive, allowing you to push your company into new areas and target your approach so that you achieve exactly what you need to.

 

The defensive approach

Data defence is the traditional approach to managing the information that your company holds. It’s all the regular things that have to be done with large amounts of data, such as maintaining security to make sure none of it leaks or is compromised. It’s the governance of data, the everyday handling of it and the processes around it.

This also includes ensuring privacy and making sure that the quality of the data is up to scratch. These are certainly things that have to be done with data that is gained in a commercial context, and many of them are done to make sure that your business falls in line with whichever set of regulations you have to adhere to.  It’s a case of preventing data from becoming a problem – rather than seeing it as a valuable asset.

This is the approach that many companies take towards data, and the one that can seem to be sensible and correct. That is, until you look further than the data defence attitude and closer at what could otherwise be done. There are opportunities to take the data that you have and use it to push your business on to the next step.

 

Go on the offensive

Being on the data offensive is about taking the wealth of information that you have at your disposal and exploring the possibilities of what it can do for your business in a proactive sense. Whereas data defence is about making sure that everything is in order, data offensive sees you pushing the boundaries and creating new opportunities.

The data that you have at your disposal can open doors for your business that were closed before. This information can support marketing and help to target outbound campaigns, making sure you are reaching the right people in the right way. In turn, this helps to build new revenue, all of which can lead to further data being gathered as time goes on.

Data management can be at the forefront of your company’s strategy rather than being something that simply has to be done. In the modern, digital world the companies that are using data well are those that are harnessing its power and using it to change their behaviour and the way they work. Data is driving their behaviour and they are allowing it to take the lead rather than letting their existing behaviour govern the way data is collected and protected.

 

A light in the dark

There is another kind of data out there that might not seem so full of opportunity until it is put under the microscope and given a closer look.

Dark data, as it is known, is the information that tends to be ignored by businesses and just builds up in the background over time. This could be server logs, data about old employees, and outdated login information, for example. In his book Dark Data: A Business Definition, Isaac Sacolik describes it as “data that is kept ‘just in case’ but hasn’t (so far) found a proper usage.” (1)

Much of this data will be seen as having little or no value to your firm, and simply something that is given the minimum amount of attention to make sure it is secure and stored correctly. But harnessing this data can be a big step in the process of moving towards data offensive and taking your company forward.

Any business that finds itself in possession of a significant amount of dark data needs to look at how to harness the opportunities that it can create, and how to capitalise on that information and turn it into something proactive rather than letting it impact your business’ resources.

While dark data can be turned to good use and create opportunities, the failure to do this could pose a risk to your company. Instead of letting it become a burden on your business, why not turn dark data into something positive?

Most companies are currently stuck in the data defence approach, but there are new solutions to this problem that can put you on the offensive. Dark data could be the key to where you go next, helping you to explore new avenues that you hadn’t thought of before. This approach will become even more effective as data analytics tools become standardised and the ability to pull information from the unlikeliest of sources increases through technology such as IoT sensors.

There is a wealth of information that any company builds up over time, and the choices are either to let it become a drain on what you do or harness the power that it can give you and allow it to take you forward.

 

References:

• http://www.cio.com/article/2686755/data-analytics/the-dangers-of-dark-data-and-how-to-minimize-your-exposure.html

 

 

Image provided courtesy of KamiPhuc

 

Does Big Data Suit Your Law Firm?

This is the third in a series of posts about our whitepaper titled “Building a data driven professional services firm” which is all about how to be data driven, not data wary.

In this post, we are going to look at whether big data is right for all types of law firms, but for the full detail – you’ll need to visit our website to access the whitepaper in full.

Data analytics is useful for all organisations, but it depends how you use it.

For high street firms, we see big data being an incredibly useful tool for managing a large list of transient customers, who might contract a service from you for a relatively short period of time (I.e. a property purchase) – then never engage with your company again.  How do you keep track of those customers?  How do you ensure you are the go-to firm when they come to sell that same house?  What about when they need a will writing?

Being able to capture this information within a CRM tool and analyse the data to see where you should target and which marketing methods work best means that

For B2B companies with large clients, analytics can be helpful in preparing individual reporting back to the clients – as the billing information will be vastly more complex for multi-year, multi-service contracts where fees are generated across a range of different departments.  Reporting helps these clients to stay on top of their legal partner’s fees, understand how their chosen firm is performing against KPIs and ensure that firms are explaining where their fees are being generated from.

For larger providers who operate at scale such as Alternative Business Structures (i.e. multinational insurance companies offering legal services), big data gives these organisations the ability to monitor their entire operations and make efficiency changes that could mean the difference between a 1% profit increase or decrease.

In our whitepaper, Martyn Wells, IT Director at UK leading law firm Wright Hassall, offers his views on how data analytics is changing service delivery in the legal sector.

Martyn highlights how smart interfacing will become more of a requirement as customers want to natively instruct their legal partners from inside their own ERP systems, or handle invoices through their own procurement tools without having to separately pick up the phone to instruct a lawyer.

This means that lawyers have to be able to integrate with these systems and be up to date with the technology being used by their clients.  And it means that data has to be able to flow through these different systems in a safe and secure manner.

Wells also cites that data will be useful for firms operating a fixed price model, as access to data tools will enable legal organisations to closely monitor fees and associated activity being carried out by lawyers to ensure profit margins remain at an appropriate level.

For the full whitepaper, and to read about how Wright Hassall use business analytics tools to create client dashboards for their customers, visit our website to download the report.

Designing data into professional services firms from the start

 

When embarking upon a new big data project, professional services firms can often get bogged down in the amount of existing governance regulations and processes already in place across the business.  “We can’t do this, because we use system XYZ”, or “This won’t work because we can’t expect our frontline staff to input data daily”.

There can often be so many blockers to a new data tool.

That’s why we interviewed leading UK law firm Wright Hassall’s IT Director, Martyn Wells, about his views on integrating data into an existing business and what could be done if data was designed into process from the start.

We have just launched our whitepaper titled “Building a data driven professional services firm” which is all about how to be data driven, not data wary.

By designing a new firm from the ground up, businesses could be fully data driven from day 1, harnessing data services to refine operations, drive marketing initiatives and monitor trends.

More importantly, it could

It could affect the time it takes to make a decision; by utilising big data tools to pull information from multiple sources in seconds.

Accuracy could be improved by always backing up decisions with data, rather than relying purely on intuition or anecdotal experience.

Systems and tools would be different as firms moved away from paper based methods and legacy systems through to newer analytics tools to conduct their decision making.

The information professionals consult to make their decisions may be different if firms were able to draw on many different sources at once.

The people usually approached for insights on a decision might be different.  For instance, if decisions to increase staff levels were usually based on a conversation between HR and Managing Partners but with new resourcing technology, firms could predict staffing requirements based on past data trends and compare it with the firm’s profitability projections, then the decision might then be based on a percentage of firm profitability rather than a consensus between Managing Partners.

Martyn Wells of Wright Hassall highlighted how the multi-generational workforce of many professional services firms can affect technology and big data adoption – due to the different training needs and culture (and how open each generation is to learning about new technology).

Wells also commented in the whitepaper on the balance that professional services firms maintain between legally trained staff (lawyers) and their business support staff (IT, HR, Finance etc).  Data analytics is a way for business support staff to provide better services to enable their lawyers to deliver the most efficient service possible, reducing time to collate and deliver data insights.

To find out more about being a data driven professional services firm, download the full whitepaper from C24 at our website to read Martyn Wells’ insights.

berg Solicitors: Making Smart Decisions in the Legal Sector

Legal firms have always used data to make better business decisions.  But now it’s getting easier and quicker to collate data into meaningful insights from which partners can make executive decisions.

Ian Brownhill, Finance Director at leading Manchester-based law firm berg, has recently implemented a new approach to data management by extracting data across the firm’s core business applications to draw new insights from the combined information. This is just one of the innovative approaches berg has taken, focusing on core values as the imaginative law firm which in 2015 has celebrated its 35^th year with a growing national profile and client base.

“Our existing Practice Management System already included a degree of reporting functionality,” commented Brownhill, “however it didn’t integrate information from other sources such as spreadsheets created by staff or data coming from other applications.  In order for the information to be presented simply and concisely, we needed to collate data across our systems into one output, giving us a single version of the truth.”

Dealing with the mass of data

berg has responded to a situation that many firms are still struggling with.  Law firms now have sophisticated systems in place that generate masses of data, but are only just starting to pull this information together rather than relying on application-specific reporting that doesn’t integrate with other application data.

So data is now abundant, but it is not being harnessed. 

One of the reasons behind this data paradox, says Brownhill, is that many Practice Management Systems designed for the mid-market legal sector do not include mature reporting capabilities, meaning that in order to access integrated reporting functionality a firm would need to purchase expensive enterprise legal software or completely overhaul their legacy PMS platform; both of which are costly and disruptive exercises.

Law firms in particular face a growing problem when it comes to managing data; primarily due to the fact that they collate huge amounts of client data, in addition to their own data generated from day to day business operations.  Firms are now looking to harness this data to gain a more holistic view of their organisations’ operations.

Big data is a behaviour; not just a technology

In addition to harmonising existing financial and operational data, the big data trend is driving firms’ behaviour; encouraging them to mine for data across each function of their business.  Business development and marketing departments are now recognising that business analytics data showing customer trends, purchasing quirks and campaign performance can ensure that revenue generation activities are more successful and targeted.  This is also a focus for Berg, as Brownhill commented, “Using data tools to bring our management reporting overview documents down from 20 pages to a simple one pager has been a huge help to our business in achieving high level visibility of our business, however harnessing information that we already have within our systems to aid with marketing and business development activities is the natural next step – and is where business analytics really starts to impact on revenue generation.”

Moving beyond the PMS

Data held within PMS systems delivers some degree of insight to Managing Partners, however when that information is combined with outputs from the CRM system, invoicing and payment applications and outbound marketing results, the information rapidly becomes a source of valuable insight that can help teams with creating sales strategies, assessing client payment probability and recovering historic debt.

The future of data in the legal sector will inevitably see reporting functionality extended out to firms’ clients.  Some companies already offer functionality to clients allowing them to access portals for viewing updates on their own cases; however sophisticated analytics tools will soon enable partners to share real-time KPI and case reporting to customers within a secure system to keep clients updated on their terms, rather than those of the firm.

David Ricketts, Head of Sales at legal hosting and analytics specialist, C24 Ltd, sees extending visibility to end clients as a crucial step for law firms competing with online providers.  “Online service providers are already very adept at providing real-time reporting to clients,” commented Ricketts, “and traditional firms are now able to use clever analytics tools to combine data and present it back to clients securely – to ultimately improve the wider customer experience”.

PMS platforms will naturally look to build analytics capabilities into the PMS application from the ground up, rather than reporting being an add-on service to an existing tool.  This will allow for the integration of multiple external data feeds to add new insight to existing information – to enable better business decision making at every level within the modern law firm.

 

Access the full case study at C24’s website.

 

About the author

David Ricketts is Head of Sales and Marketing at C24 Ltd, a specialist applications hoster with a particular focus on the legal sector.

Data: Moving from Ordinary to Visionary

 

Management information reporting is pretty standard now in all companies – after all, if the management team don’t know their key financial data points then there are probably more important concerns to focus on than how to integrate data analysis into other parts of the business.

Management information (MI) can span across the finance and operational departments, looking at staff KPIs, attendance records and revenue positions.  MI reporting can pull in data from the transaction processing systems, e-commerce platforms or financial applications – to give a view of the overall health of the business.

Business intelligence looks at taking this structured, often static information and making it more valuable and wider in its perspective.  Financial information can be combined with other data sets to provide insights that benefit not just the executive and financial teams, but also marketing and sales divisions to help drive their activities.

Moving from the ordinary to the visionary is about how to take management information and make it into business intelligence. 

 

How can information be continually made more valuable?

Business intelligence programs seek to amalgamate all of a business’ data into one system, in order to be able to cross-reference trends for deeper analysis.

Many tools now exist that can mine text across petabytes worth of documents to make data retrieval quick and easy – such as mining through emails to see how many times certain products were mentioned across a set period of time to determine potential product issues or popularity trends.

Text mining can be particularly helpful for support departments in reviewing and improving their operations.  Being able to mine the text of thousands of support calls enables management to better spot problems or identify breakdowns in support.  Once these issues can be identified (or a process for identifying issues has been formulated) then trend analysis can be utilised to spot ‘triggers’ to certain scenarios – such as an internet provider’s support calls may rise during bad weather at weekends when more people are surfing the net rather than braving the outdoors.  This could lead the internet provider to recruit more staff at weekends dependent on weather forecasts to reduce call waiting times when lines are particularly busy.

Business intelligence (BI) activities involve the collating of historical data, real-time data and future predictive analytics.  BI doesn’t just look at one set of static data, it combines data from different timeframes and scenarios to build a more accurate picture of the business through information.

For instance, a law firm we work with is looking at how they can combine all of their CRM data (which is relatively static on one level, but fluid in content at another level as new sales opportunities are inputted), with their prospect marketing database (such as e-mail distribution lists, e-mail tracking software data and event attendance).  Layered on top of this information will be data flowing in from their social media platforms, primarily LinkedIn and Twitter, in order to build a more holistic view of their business development activities.  Once this information is centralised, it is then easy to delve into trends such as uncovering the percentage of prospects that are converted to customers each month, what percentage of new customers come from their prospect list, and what percentage come from other sources.  Based on this information, the firm can then predict what revenue values mining this list of prospects will potentially yield in the future (i.e. anticipated monthly new customer revenues).

This data could then be of interest to not just the marketing division but also the finance department, showing how business intelligence can create data insights that are valuable across multiple departments.  This in turn encourages more sharing of data between departments, as the potential for new insights means better information output for each division.

Finance and marketing divisions sit on fairly opposite sides of the business.  However, combining CRM data with key financial information would enable the business to work out a number of key insights which could help them to better understand how they do business and what their customer base looks like.

Being able to understand the average revenue position per customer would help you to identify whether the business has too many customers with low levels of spend or in fact too few customers, each with a precariously high (and potentially business-damaging) average level of spend each.

CRM information combined with financial data can help companies to understand churn rates across their customer base, and what this in turn costs the business when customers leave.  It can also help to identify operational costs per sale for each customer – does one customer incur higher expense claims across your employees?  Or is the geographical location of a certain customer significantly reducing margin levels due to high travel costs?

Without business intelligence, this management information and fluid marketing data would be kept separate within the business.  The data would be there, but the value would be missing.

Is your law firm marketing up to scratch? Let big data whip you into shape.

Whilst many businesses are now leveraging big data for management reporting, the real innovators are looking at how data can be used to drive revenue growth and improve marketing effectiveness.

Analytics solutions can be deployed across the entire organisation, but in the business development department, big data really comes into its own.

Most marketing efforts within law firms focus solely on the Practice Management System, extracting data about existing or prior clients.  But what about before a client becomes a ‘client’?  How is data about prospects and web visitors tied into existing client information?

Integrating data from business development activities such as email marketing campaigns with PMS information can deliver a holistic view of marketing campaigns; from pressing the ‘send’ button through to billing clients.

We were recently doing some planning about how big data can benefit marketing activities within legal firms and came up with a number of ways that big data can be employed for revenue generation.  Below are some examples of both where our clients are already using analytics and future plans for big data within their law firm.

 

Using big data throughout the marketing lifecycle

 

Developing Prospects

Firms are now recognising that data within the PMS system alone is not enough for developing a healthy pipeline, but often the two sets of data (pre-PMS and post-PMS) are kept separate whereas analytics can unify this information.

• Google analytics data can be extracted and combined with existing CRM data to see if any particular web events prompted client action.
• Email campaigns can be closely monitored throughout their lifecycle, right through to billing and ongoing customer relationship analytics.
• LinkedIn analytics can be extracted to drive greater insights about prospects and how they are connected across your organisation.
• Social media sentiment can be monitored to understand what your customers are saying about you, and what factors (posting frequency/type) result in the most interactions or followers.
• Competitor data can be analysed; across news items, web feeds and social media streams in order to understand how other firms are going to market and performing in comparison with your organisation.

 

Working Within the System

Once a customer or prospect is present within your CRM or PMS system, then it is critical to understand how they engage with your marketing activities and interact with your firm as a whole.

• Analytics can be used to run reports on what fields within your CRM or Practice Management Systems have not been completed or filled in to drive data best practice behaviour.
• CRM and PMS databases can now be linked for organisation-wide visibility.
• The efficacy of marketing campaigns can now be tracked to understand what delivers the most ROI, what resonates the most and what results in the most web traffic.
• Different marketing tools can be linked together to create a single version of the [marketing] truth – spanning lead generation applications, call data, web traffic and CRM systems.
• Gamification can be easily delivered to the sales force by creating visual and real-time dashboards of revenue performance to drive specific behaviours across your teams.

 

Managing the Existing Client Base

Revenue generation activities shouldn’t just be targeted at prospects and non-customers, business development analytics should be focused on existing clients and identifying areas to deliver more value to customers who are already purchasing from you.

• Analytics tools can help you to create client portfolio heatmaps – quickly highlighting what clients purchase and don’t purchase from you by extracting data from the PMS platform.
• By understanding where your clients are coming from, both in terms of demographics and sources of business, you can more effectively target marketing and sales activities. If the data shows that most of your business comes from referrals from other clients, then your email marketing campaigns may not be delivering worthwhile returns on investment to justify their cost.
• Uncover trends about why clients leave your firm; what activities take place prior to a client leaving? Is there a series of steps recorded in your PMS system that could point to a support issue across your firm?
• Better understand churn rates; how often clients leave your practice, how long they are clients for and the ratio of new to existing to lost clients, in order to better understand your business position.

 

The difference with many business analytics is that reporting can be done in real-time, which is critical for planning and executing marketing campaigns when time is of the essence.  Being able to quickly pull a report to understand who has opened your recent e-newsletter, then compare it against the number of new followers on LinkedIn versus how your firm is performing for overall social media followers that month, means you can change course on the fly depending on which marketing activity has proven most effective.

We know there must be many more ways that the firms we work with are starting to deploy analytics tools to their marketing functions – we’d love to hear of any suggestions!

 

To find out more about C24’s business analytics tool, Bi24, and how we work with law firms to deliver tailored analytics solutions then please visit us online at http://www.c24.co.uk/business-intelligence-3/

C24 Publishes New Case Study for berg Solicitors

C24 has just published a case study detailing their specialist work within the legal sector, working with leading Manchester law firm: berg Solicitors.

Read the full case study here about how we worked with berg Solicitors to deliver a new infrastructure platform and business analytics solution across their firm.

Win Better with Analytics

 How are sports teams using analytics to drive performance on the field?

 

We recently looked at how sports clubs and venues are driving more profitable business activities off the field, but what about how sports teams and athletes are using analytics to better their performance?

It really is eye-opening when you start looking into the multitude of ways in which sports clubs are starting to build analytics into their training sessions and matches.  One thing is for certain: analytics in sports is becoming so ingrained in day to day activities that its presence can only increase.  We are even seeing analytics coming through to the consumer level with Fitbit type trackers which are driving training behaviour through the delivery of analytics to our smart phone.

So just how are sports clubs employing analytics for better results?

 

Separate the best from the rest

Clubs are now utilising algorithms to not only help decide which players to purchase in the first place, but on which players to send onto the pitch based on a wide range of factors.

Historically, decisions about players may have been down to the coach and manager’s personal knowledge about an individual player’s strengths and weaknesses versus a particular opposing team.  However, as more data becomes available, more factors are tipping decisions in one direction or another.

Details such as player performance based on weather or pitch conditions are now starting to be taken into consideration.

 

Biometric data at a player level

UK football clubs are starting to invest in wearable technology, where sensors are placed in clothing to monitor field position and biotmetric data such as heart rate, hydration and distance covered during a match in order to deliver more holistic analytics.

Without this data, information about where a player spent most of his time on the field during a match would be purely anecdotal whereas now coaches can get real-time data about player positions in order to make decisions on the fly.

If the data is not collected in the first place, then it cannot be analysed and measured in order to spot important trends.  Without collecting the data and placing it alongside other data streams, how can a coach see what impact factors such as hydration levels or stadium capacity have on player performance?

 

Video analytics

It is now common for stadiums to have upwards of 8 cameras installed around the arena, whose core focus is on capturing information about the game – by analysing player performance during the pitch, locations, movements and general developments.  This is a huge amount of information to dissect (8 cameras recording over circa 3 hours of footage each) which means that having analytics is critical for getting a high level view of key events during the match.

 

Accuracy in umpire decisions

Analytics is playing a big part in helping umpires to be more accurate in their decisions, or at least to have a degree of data to back up their (sometimes controversial) rulings.

In tennis in the UK, we regularly see Hawkeye being employed to provide not only umpire decision clarifications but also analytics about player shot success rates.

 

Making sports safer

Clubs are now turning to analytics to make sporting events safer for their athletes, by tracking hydration levels, alongside trend analysis for injuries to predict when players should be brought off the pitch to best reduce the risk of injury.

Additionally, in sports such as rugby where there is a lot of physical contact, sensors are being employed to track how many knocks or high-impact contact situations occur to reduce the risk of serious personal injury to the player.

 

Individual performance improvement

Analytics can be utilised in sports to drive small performance increments at the individual athlete level.  IBM helped ultracyclist, David Haase, in his 2015 Race Across America, to look at the best times based on historical data for him to sleep and rest – due to headwinds and tailwinds.  This helped to make his time spent cycling more efficient, and without this simple piece of data, he would have used much more energy trying to cycle in less than optimum conditions.  As David Haase himself put it, previously, he just relied on “fitness and luck”.

In the field of swimming, athletes are utilising on-body sensors to track each component part of their training to make small efficiencies, such as monitoring stroke technique or kick frequency.  Small changes at this level can make the difference between finishing a few seconds ahead of your competitors.

 

The amateur athlete

One interesting point is that big data hasn’t just started with the large, multinational clubs and filtered down slowly to the public, there is in fact a two way trend taking place where consumers are tracking their own personal fitness at an individual level; relying on data and analytics to deliver better insights into their training regimes.  Technologies such as Fitbit are now delivering in-depth analytics across sleep, exercise, activity and nutrition to help amateur athletes track their progress and make improvements.

 

only listed a handful here.  From Nascar drivers using sensors to Olympic athletes employing “data not doping” to drive huge performance increases, analytics is becoming central to every training session and live sporting event.

 

 

Image courtesy of Melodie Mesiano.